Wednesday, October 29, 2014

Electron Paramagnetic Resonance of hair!

I wanted to switch gears a bit and do a paper on Electron Paramagnetic Resonance (EPR), also know as Electron Spin Resonance (ESR).  The paper for this weeks is

Electron spin resonance (ESR/EPR) of free radicals observed in human red hair: a new, simple empirical method of determination of pheomelanin/eumelanin ratio in hair.


Chikvaidze EN, Partskhaladze TM and Gogoladze TV;jsessionid=39B010DF34D055C5F27880DD49E628F1.f01t04

I discussed EPR briefly in an earlier post (  To review, one can think about EPR much like you think about NMR.  In a simple 1D 1H NMR spectrum parameters like the resonance frequency (the chemical shift plus any scalar couplings) and peak integrals can be interpreted to understand properties of the molecule, for instance the molecular structure of a small drug-like organic molecule.  There are similar parameters for EPR.  In EPR the resonance frequency is reported as the "g-factor."  Instead of depending on the shielding of nuclei by electrons like the chemical shift in NMR, the g-factor depends on the coupling of the spin motion of the electron to the orbital motion (spin-orbit coupling).  These days every organic chemistry textbook contains a table of chemical shifts classified by functional group.  With EPR, on the other hand, I am not aware of any standard tables of g-factors.  I don't want to suggest that the spin-orbit coupling is not sensitive to electronic structure.  Of course it is!  Spin-orbit coupling depends on which orbital the unpaired electron resides.  For metals, the g-factor is crucial.  For organic (oxygen, carbon and nitrogen) radicals, though, it seems like all g-factors are ~ 2.  Although the g-factor is not diagnostic in these cases, the coupling to magnetic nuclei are!  The unpaired electron will experience "hyperfine" coupling to nuclei, such as 14N (nuclear spin I = 1).  The electron is split into 2I+1 lines.  Hence if the nuclei is 15N (I = 1/2) the EPR signal is a doublet.  If the nuclei is 14N, the EPR signal is a triplet, but all three legs have identical height.  (As an aside, I'll mention to organic chemists that they should look at the CDCl3 signal in a 1D 13C spectrum to see an equivalent effect).  EPR spectra differ in two key ways from NMR spectra.  First, the x-axis is magnetic field (in gauss or telsa) not frequency.  Second, the y-axis is the first derivative of the absorbance.

Now that we are all experts on EPR, what is it that Chikvaidze and co-workers are measuring?  There is a branched polymer in skin and hair called melanin that controls pigmentation color.  This polymer is made of varying amounts of two monomers, called eumelanin and pheomelanin.  The former is associated with dark (brown or black) colors, the latter with red.  Eumelanin contains a O-C-C-O semiquinone and gives an EPR signal consistent with an oxygen radical (a singlet).  Pheomelanin contains a O-C-C-N semiquinonimine and gives and EPR signal consistent with a nitrogen radical (triplet).  According to the authors the measurement of the concentration of pheomelanin in skin samples is "an issue of great interest in the world" because UV-mediated breakdown of this molecule produces reactive oxygen species which "might help to explain the relatively high incidence of skin cancer among red-haired individuals."  There are assays available to determine the ratio of pheomelanin/eumelanin in hair samples that involve chemical treatments, etc.  Because these molecules are paramagnetic, it is possible to use EPR as a non-invasive assay to determine the amount of pheomelanin (ug/mg) in hair samples.

What did the authors do?  They collected 113 hair samples from their students (42 black, 28 dark brown, 27 red and 16 blond - I assume each sample is from a different student.  It is not clear if all samples are used in this study.) and divided the samples in bundles of equal mass (40 mg) and length (1.5 cm).  Because they need to make very accurate measurements of the g-factor, the authors use a standard of Mn2+ (in MgO powder).  I assume the standard is in a sealed capillary which is placed in a 4 mm EPR tube along with the hair bundle.  EPR are measured using an X-band EPR spectrometer at room temperature.

The EPR spectrum of black hair is a "slightly asymmetric singlet" with g-factor = 2.0035-2.0036.  The spectrum of black hair looks identical for each donor (data not shown).  For red hair, on the other hand, the spectrum vary depending on the donor.  The authors classify two distinct types of spectra (type I and type II) with g-factor = 2.0038-2.0047 shown in Figure 2:

The interpretation of this data is that the EPR spectrum of black hair is essentially the spectrum of eumelanin, whereas the spectrum of red hair is a superposition of eumelanin and pheomelanin.

The authors used microwave saturation to filter one of the components of red hair.  Let me try to explain saturation succinctly.  If the rate of spin flips between the spin-down and spin-up state is faster than the rate of relaxation back to the ground (spin-down) state, then the intensity of the signal is attenuated by saturation.  The rate of spin flips depends on microwave power.  The relaxation rate depends on R1 (= 1/T1).  Let's say there are two signals in the EPR spectrum.  One has a small R1 (aka large T1, aka slow relaxation) and the other has a large R1 (aka small T1, aka fast relaxation).  We can then choose a microwave power such that the rate of spin flips is larger than the small R1, but smaller than the large R1.  So the slow relaxing signal is saturated and maybe even disappears.  One can play this game with a 10 uM solution of TEMPOL radical under an atmosphere of air (which includes paramagnetic oxygen that will increase R1) or nitrogen.  At high microwave power the slow relaxing (large T1) nitrogen atmosphere sample will saturate and give no signal, but the fast relaxing (small T1) air atmosphere sample will not.

Figure 3 shows the EPR spectrum of red hair as a function of microwave power:

The authors interpretation is that "the triplet (hyperfine coupling = 0.372 mT, g-factor = 2.0055) .. evident after saturation of the singlet at maximum microwave power, corresponds to pure pheomelanin in the .. spectrum."

Now the authors are prepared to address their main goal: determine the ratio of pheomelanin/eumelanin in hair.  Given that pheomelanin has a g-factor of 2.0055 and eumelanin has a g-factor of ~2.0036, the authors hope to use the experimental g-factor of hair to determine the ratio.  Normally, one would make a calibration curve with different ratios to test the fitness of this method. Not so simple in this case.  One can mix different ratios of red and black hair, if you assume black hair is pure eumelanin.  Figure 4 shows the calibration curve.

Using data from Ito et al. (Pigm. Cell Melanoma Res. 2011 24, 605) that correlates hair color to concentration of pheomelanin in ug/mg, the authors make another calibration curve to convert the measured g-factor into pheomelanin concentration, shown in Figure 7.


My only beef with this paper is that the accuracy and precision of this method to measure pheomelanin and the ratio of pheomelanin:eumelanin is not addressed.  Let me state it another way.  Let's assume you can distinguish hair that contains 0.8 ug/mg pheomelanin from hair that contains 4.8 ug/mg.  Can you distinguish 2.4 ug/mg from 2.5 ug/mg?  To answer this question I did some simulations in MatLab using EasySpin ( a supercool simulation program.  My script is at the end of the blog.

The first plot shows the simulated EPR spectra of blond (in blue) vs red (in green) hair using data from Table 2 in the paper. 

Using the zero crossing to estimate the g-factor for the blond hair equals 2.0035 and for the red hair equals 2.0037, which is somewhat smaller than the 2.0046 from the Table 2 of the paper.  OK fair enough.  We can tell blond from red hair using the g-factor.

Two different red hair samples with pheo/eu% equal to 59 (blue) and 54 (green) look identical to me (see below).


Maybe I'm screwing something up with my simulations, but based on these results I am skeptical that X-band EPR can pick up subtle difference is pheomelanin:eumelanin.  Q-band (35 GHz) is a different story, though.  Signals at different g-factors no longer overlap and using double integrals, it may be possible to estimate pheomelanin concentration.  Below is the Q-band simulation of pheo/eu% equal to 59 (blue) and 54 (green).  I also assumed smaller lwpp to exaggerate the transitions.

Overall, I like this paper because it made me think about EPR and play with EasySpin.  It also got me worried about hair in my EPR cavity!  I'll have to keep the gingers away from my instrument.


EasySpin MatLab script

% Mixture of pheomelanin and eumelanin
% based on data from Chikvaidze et al. MRC 2014


% Experimental parameters
Xp.mwFreq = 9.43;
Xp.Range = [334 338];

% Component 1
Eu.g = 2.0035;
Eu.lwpp = 0.5;

% Component 2
Pheo.g = 2.0055;
A = 0.372;
Pheo.A = mt2mhz(A);
Pheo.Nucs = 'N';
Pheo.lwpp = 0.5;

% Relative abundances
Eu.weight = 0.46;
Pheo.weight = 0.54;

% One call to pepper
[B1,spc1] = pepper({Eu,Pheo},Xp);

% Relative abundances
Eu.weight = 0.41;
Pheo.weight = 0.59;

% One call to pepper
[B2,spc2] = pepper({Eu,Pheo},Xp);

plot(B1,spc1,B2,spc2); Chikvaidze, E., Partskhaladze, T., & Gogoladze, T. (2014). Electron spin resonance (ESR/EPR) of free radicals observed in human red hair: a new, simple empirical method of determination of pheomelanin/eumelanin ratio in hair Magnetic Resonance in Chemistry, 52 (7), 377-382 DOI: 10.1002/mrc.4075

Monday, October 13, 2014

You don't need that big expensive magnet to do NMR!!!

As chemists we often focus on parameters like chemical shift, scalar coupling and integrals that can be measured in an NMR spectrum and interpreted to understand qualitative and quantitative information about molecules.  There are applications where these parameters are less important and the longitudinal (T1) and transverse (T2) relaxation time constants and/or the self-diffusion coefficient (D) are critical.  A lot of these applications do not involve the types of samples that organic chemists or biochemists prepare (~600 uL in a 5 mm NMR tube).  In fact, sometimes T1, T2 and D need to be measured in extreme environmental conditions.  You can't drag your 11.7 T magnet to the south pole!  Even in more benign environments, a big magnet is not necessary for T1, T2 and D measurements needed for tasks like food characterization and oil-well logging.

Today I am going to discuss two papers that explore NMR without a big and expensive magnet!

The first paper is

"Ultra-low-field NMR relaxation and diffusion measurements using an optical magnetometer"


Ganssle PJ, Shin HD, Seltzer SJ, Bajaj VS, Ledbetter MP, Budker D, Knappe S, Kitching J and Pines A.

Angew Chem Int Ed Engl. 2014 53 9766-70
doi: 10.1002/anie.201403416

The authors design and demonstrate an ultra low field (ULF) NMR capable of performing industrially relevant measurement (T1, T2 and D) for the characterization of mixtures of hydrocarbons and water.  The authors claim that their instrument is the first step towards a compact, inexpensive and robust NMR sensor which operates at the Earth's magnetic field. 

How does this work?

Conventional NMR detectors use a coil to detect transverse magnetization.  The ULF NMR uses a magnetometer like what is in your cell phone as a compass.  The specific magnetometer is optically detected (the author's do not really explain the detector in this paper).  I don't pretend to understand all the details of this detector, which is called a spin exchange relaxation-free (SERF) configuration magnetometer.  The important thing to understand is that the detector measures longitudinal magnetization (along the z direction), in contrast with traditional NMR coils.  In fact, during acquisition, a series of 180 degree pulses are applied to sample to flip the spins between the +z and -z direction.  The authors convert the "average magnitude of change in magnetometer signal in response to a pi pulse" into a sensible signal.   

The authors want to design "a NMR sensor which operates at the Earth's magnetic field", but for now they have to make a few compromises to get a prototype.  First, there isn't much longitudinal magnetization in samples polarized by the Earth's magnetic field, so the authors apply a "pre-polarizing" 2 T field.  Second, the sample chamber is not really at the Earth's magnetic field, which (according to Wikipedia is at 25–65 uT (microtesla).  By the way, a strong refrigerator magnet has a field of about 10 mT.  At any rate, the chamber is designed to have no magnetic fields - there is some sort of special shielding to remove the Earth's magnetic field.  Then a weak "bias" magnetic field (50 uT in this case) is applied to the chamber.  This field is designed to be turned off during detection (the SERF detector has optimal response at zero field) and during pulses.  The reason for turning off the field during pulses is so that "the device does not need to be re-tuned when the bias field is changed."   Overall, their set up looks like the following:

The pulse sequences used to measure T1, T2 and D are the following:

If you study these pulse sequences, they will make a lot of sense.  The T1 measurement does not use the inversion recovery pulse sequence, instead longitudinal relaxation time constant is measured "as an exponential decay of the spin magnetization as a function of an increasing delay time between the sample pre-polarization and measurement."  You also see the unusual detections strategy.  Longitudinal magnetization is flipped between -z and z by a pi pulse.  The T2 measurement is a standard CPMG train.  "The inter-pulse spacing (tau) is held constant and the number of pulses (n) is varied."  Diffusion is CPMG with a gradient.

One thing I find pretty cool about this set up is that it uses conventional 5 mm NMR tubes!

What do the authors measure?

They record the relaxation time constants (T1 and T2) of some common solvents: water, methanol, ethanol and hydrocarbons at 0.5 G and 37 C.  They also make mixtures of hydrocarbons and water.  How did they do that?  These liquids are immiscible!  In fact, they used "a coaxial insert which separated liquid in a smaller, 3.3 mm NMR tube from the liquid in a standard thin walled 5 mm NMR tube."  I'm not sure I would call that a mixture, but why split hairs!  The data looks like the following:

Finally the authors can make 2D plots of T2 v T1 or T2 v D to demonstrate how readily these solvents can be distinguished based on these relaxation properties:

The authors conclude that this device is an "important first step towards the development of compact, inexpensive devices which can take advantage of the Earth's high homogeneous ambient magnetic field."  They acknowledge "the limitations present in these experiment ... are artifacts of the design of the device" but feel that they make a "compelling case for future research".

I think the device described in this publication is interesting and important.  I have a few questions, though.  How long does it take to make each T1, T2 and D measurement shown in figure 3 (each dot on the curve)?  Can T1, T2 and D distinguish miscible liquids, such as water-methanol or water-ethanol?  I work at a University and the proof of the vodka is a major concern on football days!  Finally, how big is the instrument, really?  It is hard for me to get a feel for the size based on Figure 1.  It looks almost as big as a superconducting NMR magnet.

The second paper is

"Scalable NMR spectroscopy with semiconductor chips"


Dongwan Ha, Jeffrey Paulsen, Nan Sun, Yi-Qiao Song and Donhee Ham

In contrast with the first paper, which described an unconventional detection scheme, this paper describes a miniaturized NMR system that is ~12 cm^3, weighs 7.3 kg and can perform 1D 1H, multi-pulse and heteronuclear experiments.  By contrast, a commercially available system like the Picospin45 ( is 20.3 cm x 14.6 x 29.2 cm, weighs 4.7 kg and can only do 1D 1H.  The major innovation by the authors is the miniaturization of the electronics into a 4 mm^2 chip.  The technical details are best understood by an electrical engineer, so I won't explain too much.  The net result is a system that looks like the following:

Obviously there is quite a bit missing from the picture, but the penny on the left gives a general idea of the size of the system.  The Larmor frequency is 21.8 MHz.  Samples are 1 mm capillaries with ~0.8 uL of sample.  What can the system do?  Figure 3 shows 1D 1H for 7 small molecules (acquisition times on the order of seconds to minutes).

Frankly, this data looks like 21.8 MHz NMR spectra.  The magnet is shimmed to 0.13 ppm resolution (~2 Hz).  So you can make out 7 Hz couplings, but small couplings or lines closer than ~0.1 ppm blend together.  The spectra of aspirin, serine and glucose are not useful for chemical characterization.

One of the advantages of the design is pulse programming.  The ability to control pulses and delays enables the authors to go beyond traditional 1Ds and do multidimensional NMR.  Figure 4 shows the JRES and 2D phase sensitive COSY on neat ethanol and 1.5 M alanine dissolved in D2O (acquisition times are 15 and 73 minutes, respectively).

The authors can also collect HSQC and HMQC on 13C enriched methanol in 17 and 34 minutes, respectively.  Note that there is no decoupling during acquisition (t2), meaning the peaks are split by the 1JCH.

The authors round the paper out with a relaxometry experiment on a crude oil sample.  They also introduce a clever processing hack to handle temperature fluctuations, which present a "significant obstacle towards portable NMR."  Their solution deserves a longer explanation in this blog post, but lets face it, it is getting way too long.


To wrap up this post, I'll note that I am not convinced that either system discussed above or a commercial benchtop NMR (from PicoSpin, Magritek or Nanalysis) can ever replace a trusty 400-600 MHz NMR for resonance assignment in organic chemistry or biochemistry.  I will concede that not all chemical characterization requires a 400-600 MHz NMR.  To paraphrase John Edwards from Process NMR associates at the MestreNova Users meeting prior to the ENC this year "if your spectrum looks like crap at 400 MHz, it won't look too much worse at 90 MHz, so why waste time on a superconducting magnet."  The authors of the papers I reviewed today present two novel NMResque instruments capable of making measurements nearly identical to a high field superconducting system.  The trick will be to continue to develop these systems and find applications where these systems outperform conventional systems.  


Ganssle, P., Shin, H., Seltzer, S., Bajaj, V., Ledbetter, M., Budker, D., Knappe, S., Kitching, J., & Pines, A. (2014). Ultra-Low-Field NMR Relaxation and Diffusion Measurements Using an Optical Magnetometer Angewandte Chemie International Edition, 53 (37), 9766-9770 DOI: 10.1002/anie.201403416  

Ha, D., Paulsen, J., Sun, N., Song, Y., & Ham, D. (2014). Scalable NMR spectroscopy with semiconductor chips Proceedings of the National Academy of Sciences, 111 (33), 11955-11960 DOI: 10.1073/pnas.1402015111

Friday, April 18, 2014

ENC 2014 Post 1

SPECIAL NOTE:  I wrote this post at the ENC, but for some reason it never got posted.  (I blame the crappy wi-fi in my hotel!).  Sorry ...

Day 1 of the 2014 ENC

The first session was the Laukien Prize session.

The prestigious Laukien prize is given to recognize excellence in experimental nuclear magnetic resonance published within the last three years.  The 2014 Laukien prize is awarded to a group of six leading solid-state NMR spectroscopists for their development and application of magic-angle spinning (MAS) ssNMR experiments for the determination of 3D protein structures and the study of associated molecular dynamics processes.

The winners are:

Marc Baldus - Utrecht University
Mei Hong - Iowa State University
Ann McDermott - Columbia University
Beat Meier - ETH Zurich
Hartmut Oschkinat - Leibniz-Institute (FMP) Berlin
Robert Tycho - NIH

Each winner was given 15 minutes to give a research overview, which was very exciting!

The second session was called "Electron Meet Nuclei", which was a cute title for a DNP session.  The organizers pointed out that 2014 is the 70th anniversary of the discovery of magnetic resonance (MR).  MR was discovered in 1944 by Zovoisky at Kazan University, USSR, who observed the EPR signal of CuSO4 and CuCl2.  The session featured a great talk by Bob Griffin from MIT and I really enjoyed a whirlwind of a talk by Mei Hong about ssNMR to probe plant cell wall structure.

After lunch there was a poster session.  I always love the poster session.  I learn so much.  I really enjoyed a plant metabolomics study of watermelon.  (Poster 167) The presenter (Iqbal Mahmud from Claflin University in South Carolina) looks for biomarkers that correlate with resistance to Powdery Mildrew (PM), a nasty fungus that ruins crops and costs growers a lot of money.  He found several and made a hypothesis regarding the pathways upregulated in PM resistant varieties.  Now collaborators at the Department of Agriculture are treating watermelon to engage this pathway to see if it confers resistance.  What I really liked about his poster was the experimental design.  The presenter and collaborators made grafts to assess the translocation of biomarkers, instead of just hunting through watermelon juice with no hypothesis.  I guess you could call this work "untargeted metabolomics", but, by good experimental design, the authors certainly increased their odds of finding a relevant target!

Day 2

The AM session began with the presentation of the JMR awards.  2014 is the inaugural year of this award, which is picked from abstracts submitted from graduate students and post-docs and includes a one year subscription to JMR and $350.  The winners are

Joseph Courtney UIUC
Michael Loretz ETH Zurich
Moritz Zaiss German Cancer Research, Heidelberg


The first session was "Biomolecular Structure and Function".  All talks were outstanding.  I was especially impressed with Jim Prestegard's talk "Sparse-Labeling and Long-Range Constraints: Structure and Function of Glycoproteins".  Professor Prestegard discussed work in his lab using selective labeling and PRE to explore how glycan structure and dynamics impacts function of glycoproteins, in particular, Immunoglobin G (IgG).  Glycoproteins are notoriously challenging to study because the heterogeneity, but the CCRC in Georgia has developed a number of clever tricks to hijack enzymes to selectively label glycans.  The examples discussed in this project all involve labeling galactose on a long branched glycan chain.  There are two galactoses on this glycan and there is evidence of chemical exchange broadening.  Rex measurements result in kex and some structural information on two major species.  It seems the the glycan flips between a "free" and "bound" structure.  The bound structure agrees with crystallography and the sugars are buried inside the IgG.  In the free structures, the glycan hangs out of the bottom of IgG.  A very long (microsecond) MD simulation suggests that the glycan does shuffle between the inside and outside.  Very cool work.

Next, there were parallel session.  I was torn because I wanted to hear some talks from both sessions, but I opted to stay in one room and listen to all the "Drug Design Ligand Interactions" session.  Once again, the talks were excellent.  Kevin Gardner gave a great talk, as always, and two student talks (by Quentin Chappuis from EPFL Lausanne and Johannes Bjornmeras from Stockholm U) were both riveting.  In the afternoon session, there were tutorials, including a lecture by one of the great NMR teachers in the world, Professor James Keeler from Cambridge.  He wrote a great book (which I own and read every chance I get) and posted many lectures on YouTube.  

Overall a great day!  THere is a special workshop tonight regarding the National Research Council Report on High Field Spectrometers in the US, which discusses NSF policy on mechanisms for funding and siting new high field NMRs.  A representative from NSF will be on hand.

Thursday, March 27, 2014

ENC 2014 Post 2

Another great day at the ENC.

The early AM session "Dynamics" included a very interesting talk by Cyril Charlier from CNRS, Paris.  The title is "Nanosecond Time Scale Motions in Proteins Revealed by High-Resolution NMR Rexalometry."  The concept is that it would be helpful to protein NMR people to measure T2 (and T1 and NOE) at many different fields, especially really low fields, to characterize fast time scale dynamics.  Of course, low fields means less polarization and resolution.  So you end up with lots of overlap and low signal-to-noise.  The authors realized that inside a NMR magnet -  it is only at the nominal field for a small area, then the field drops off.  So if you can design a "shuttle" system to move the sample inside the magnet you can turn a NMR at one field (say 800 MHz) to a magnet that has all fields from 800 MHz to 45 MHz.  The limitation (for the time being, at least) is that the probe sits at one spot, so you have to pulse and record at 800 MHz.  How can you use this trick.  Relaxometry.  They developed a variant of the HSQC in which you shuttle the sample up to low field for a "relaxation period" then shuttle back to acquire.  For every scan it has to jump up to low field then back down.  They also developed some theory and software to handle the combined effects of relaxation at high field (during pulses and acquisition), at low field (while it sits high in the magnet) and shuttling.  At this stage they've only reported applications to ubiquitin, but this idea is interesting and I want to see where it goes.

There were parallel sessions in the late AM.  I couldn't decide if I wanted to go to Biomolecular Structure and Function II or Hyperpolarization.  I decided to go the the Hyperpolarization, because this session featured non-DNP hyperpolarization (optical polarization, LLS and photo-cidnp).  I heard Silvia Cavagnero from UW-Madison discuss progress with her photo-cidnp system.  There were posters in the afternoon and parallel sessions on in vivo biomedical MRI/MRS and Solids. I probably should have attended the in vivo session, but by this time I was ready for a short break, so I took this opportunity to see the city and visit an old friend in Boston. 

Overall, a great day.  One more full day left and back home on Friday.  I'll probably make one more post on Friday.


PS - I'll mention that I saw the news reports on the huge fire in the Back Bay yesterday.  I just read on Twitter that two fire fighters were killed in the line of duty!  As a family member of a first responder, I am very saddened to hear about the loss of life of a fire fighter and I extend my heartfelt sympathy to the families, friends and co-workers.

Saturday, March 22, 2014

The 55th Experimental Nuclear Magnetic Resonance Conference

Hello all.

This week I will be blogging about the 55th Experimental Nuclear Magnetic Resonance Conference (ENC) in Boston, Ma.  This conference is the granddaddy of all NMR conferences and usually contains a very wide variety of talks on all sub-disciplines of NMR.

The program can be found at

I hope to give daily updates, but I don't want to make promises that I can't keep.  The hospitality suites are very inviting at ENC.  I am looking forward to a great week.


By the way, I have been slack on blogging lately due to several huge projects which are now complete.  I hope to get back to bi-weekly blog posts after ENC.

Tuesday, February 18, 2014

Hyperpolarization without persistent radicals

The paper for this week is

"Hyperpolarization without persistent radical for in vivo real-time metabolic imaging"


Eichhorn, Takado, Salameh, Capozzi, Cheng, Hyacinthe, Mishkovsky, Roussel and Comment

PNAS 2013 110 18064

There is a lot going on in this short and well-written paper.  I highly recommend that you read it yourself, because I don't quite know where to start.  I guess I have to start somewhere, so let's jump into metabolic imaging.

For most organic chemists busy dissolving their precious compounds into 500 uL of CDCl3 and transferring to 5 mm NMR tubes, it might be a shock to learn that using high end MRI scanners, it is possible to take spatially- and temporally-resolved spectra on mice (or humans).  Yes.  You can lay in a (high end) MRI scanner and someone can take an NMR spectrum of a specific anatomical region, say the brain or the heart.  Some organic chemist should ask the question - why doesn't my department buy an MRI scanner and let me (and all my lab mates) set up a reaction flask inside and take NMR spectra of little regions of my flask as the reaction proceeds?  Frankly, the spectra are crummy relative to conventional NMR.  One trick used to improve spectral quality is to use 13C-labeled material and record 13C NMR spectra.  Going back to biological samples, it is possible to measure the real-time, spatially-resolved conversion of substrates into metabolites in this technique.  This technique is called metabolic imaging. 

Sensitivity is one big problem with metabolic imaging, leading various groups (and companies, etc.) to borrow any available tools to increase signal-to-noise.  One powerful tool that is all the rage in solid state NMR of biological macromolecules these days is dynamic nuclear polarization or DNP. 

One of the best explanations of DNP is on the website of Bridge12, a company that sells hardware to do this type of experiment.

By the way, I'll mention that Bridge12 maintains a nice literature blog at

To summarize briefly, a sample is mixed with persistent radicals.  Because the unpaired electron has a much larger gyromagnetic ratio, the population difference between spin-down and spin-up states is larger, which explains why EPR is so much more sensitive than NMR.  The trick behind DNP is to use microwave irradiation to saturate the EPR signal of the persistent radicals and transfer the polarization to the nuclei in the sample, much like the classic steady state NOE experiment.  This transfer leads to an enhancement of signal.

For any clinical application, though, DNP is hard to pull off.  Because you cannot inject radicals into a patient, you have to filter them out after transfer.  Meanwhile everything is relaxing and some of the signal enhancement that you have fought so hard (and paid so much) to get is lost.  You get about a minute.  But in this minute, impressive results have been collected, allowing real-time detection of metabolic intermediates in vivo.  The authors assert that "most preclinical developments have focused on samples of neat pyruvic acid (PA) to which suitable persistent radicals are added."  PA is important because "this molecule has a central position in the glycolytic pathyway" and "is a powerful marker for cancer metabolism."   

As the title of the publication suggest the authors of this paper describe a way to take advantage of the sensitivity gains of DNP without persistent radicals.  They make tiny beads of neat PA and extract an electron by UV irradiation to make a radical.  They do the DNP experiment to enhance the 13C signal of PA.  When these beads are dissolved in water, all you get is hyperpolarized pyruvate, pyruvate hydrate and acetate (and CO2 gas).  All this extra signal make it possible to record spatially and temporally resolved 13C spectra inside a mouse and watch the formation of lactate and breakdown of pyruvate!

What do the authors actually do?

They devise a clever experimental setup so that droplets of 2 +/- 0.5 uL of pyruvic acid are dripped one-by-one into a 3 mm EPR tube ( sitting inside a EPR dewar ( filled with liquid nitrogen.  Each drop is flash frozen into a little bead ~1.5 mm in diameter.  Approximately a dozen beads are collect in each EPR tube.  I picture bubble tea in my head.  Then each EPR tube filled with frozen beads and liquid nitrogen is irradiated for 1 hour using a high-power 365-nm LED array.

What happens in this setup?  First, radical are created.  Figure 1B and C show the X-band EPR spectrum of natural abundance PA beads and [1-13C] PA beads at 77 K after 1 hour of UV irradiation.

For readers unfamiliar with EPR, it helps to think of EPR in terms of NMR, except EPR focuses on unpaired electrons.  The x-axis is magnetic field instead of frequency (or ppm) because in EPR the magnetic field is swept during the experiment.  The y-axis is the first derivative of absorbance instead of absorbance.  At the point on the x-axis where the signal switches from positive to negative is the maximum of the absorbance.  If you study Fig 1B, you will see four such crossing.  If you study the intensity of the bands you can convince yourself that the absorbance spectrum is a quartet.  The reason is that a delocalized unpaired electron is coupled to three equivalent protons (the methyl group of PA).  As a control, the authors also make beads with 13C enrichment at the 1 position.  In this case, the unpaired electron is coupled to one 13C nuclei and 3 equivalent protons.  The absorbance spectrum is a doublet of quartets.  If you study the EPR spectrum in Fig 1C you can convince yourself that you see a doublet of quartets. 

What is actually going on in the beads upon UV irradiation in not consequential for this publication.  To quote the authors "in aqueous solution, PA undergoes efficient photodecarboxylation. ... The radicals produced by the low-temperature UV irradiation of the pure acid  ... are most likely related to intermediary products postulated for this photodecarboxylation mechanism."  In summary it does not matter why, but the authors can produce PA radical at concentrations of 15 mM.  They get the concentration from quantitative EPR.

Approximately seven frozen beads of [U-13C] PA are dissolved in ~500 uL of D2O to make a 900 mM solution, which is transferred to 5 mm NMR tube.  The authors record a 1D 13C NMR spectrum with no 1H decoupling on a 400 MHz NMR.  The interscan delay equals 180 s and the number of scans equal 512 for a total acquisiton time ~17 hours.  The result is shown in Fig. 2.

The authors assign several 13C resonances to pyruvate, pyruvate hydrate, acetate and CO2.  The authors interpretation of this result is that upon dissolution, PA radical decomposes to CO2 and acetate!  There is no EPR signal upon dissolution and the 13C T1 are the same as non-UV irradiated PA.  Together these data indicate that there is no radicals and these samples can be injected or perfused into live animals.

To get hyperpolarization, though, you still have to do the microwave saturation experiment.  The authors state that using their system, 13C polarization of 10% can be achieved in 2.5 h at 5 T and 1.2 K using 50 mW microwave power.  I have no idea if that is impressive or not.  It sounds very expensive, though.  By way of comparison, using traditional persistent radicals, 13C polarization of 60% can be achieved in the same amount of time.

To demonstrate the potential of their method, the authors collect in vivo metabolic images on a mouse.  80 mM hyperpolarized pyruvate solutions are prepared from UV-irradiated PA beads.  A 300 uL bolus was injected into mouse femoral vein.  A 13C spectrum localized in the mouse head was measured every 3 s for 75 s.  Holy crap!  A 13C spectrum every three seconds!  Figure 4A shows the
spectra.  The inset spectrum is a sum projection (I assume).    

What is more is that the authors can collect metabolic images 5 mm^3 spatial resolution, 3 s time resolution.  Fig. 4B and C show 13C images using interleaved selective excitations of pyruvate (B) and lactate (C) superimposed on 1H anatomical images of the mouse head.  

Figure 4 is very impressive and it is clear why the authors think they are onto something.  Endogenous DNP is clearly a huge step towards routine clinical applications.  I look forward to following this field. 

*** citation code

Eichhorn TR, Takado Y, Salameh N, Capozzi A, Cheng T, Hyacinthe JN, Mishkovsky M, Roussel C, & Comment A (2013). Hyperpolarization without persistent radicals for in vivo real-time metabolic imaging. Proceedings of the National Academy of Sciences of the United States of America, 110 (45), 18064-9 PMID: 24145405


Monday, February 10, 2014

Papers I am reading ...

It has been a big week at Sit and Spin.  Last Tuesday morning just after I posted my review of an Angew. Chem. paper on NMR of very large protein complexes (, I jumped over to twitter to publicize the blog.  I don't remember the exact chain of events, but eventually my blog was mentioned by @SeeArrOh, an organic chemist and blogger ( with a wide readership.  As a consequence, the blog got more hits in one day than I had in the previous three months combined!  

In parallel, I saw an interesting news article on Nature ( highlighting the correlation between citations in research blogs and citations in the scientific literature.  This article reminded me why I got into the blogging game.  I think there is a lot of great research being done by hard-working and thoughtful scientists in the field of NMR.  I am concerned that the broader community of chemists is not aware of this work, or at least as aware as they are about work in other branches of chemistry.  Perhaps, in some small way, this blog can help to remedy this problem.  

Additionally, the Nature news article alerted me to the site  I am ashamed to admit that I was unaware of and underlying the movement underway in science communications.  This site is such a great aggregate of information.  I have spent so much time digging through it that I went ahead and applied for an account.  I would be honored if the editors include this blog.  

Of course with added attention there will be added pressure to write more posts.  It takes me a while to write a complete critique.  It probably takes almost as much time as it took me to make powerpoint slides for journal club in group meetings back when I was a post-doc.  And I only had to do that a few times per year!  I am trying to get a blog post out every other week.  

In case I don't get the opportunity to discuss all of them, here is a list of papers in my "to blog" pile.  I picked these out of the most prominent journals that publish NMR papers.  The criteria I use is the following: "Does the title and abstract seem interesting to a wide audience?"  If anyone out there finds something that I am missing, please contact me.  

Here is my list.  I'll try to get to two or three of these in the next month or so.

Hyperpolarization without persistent radicals for in vivo real-time metabolic imaging.

Eichhorn et al.

PNAS 2013 110 18064

NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers.

Sekhar A, Kay LE.

PNAS 2013 110 12867

Diastereotopic splitting in the 13C NMR spectra of sulfur homofullerenes and methanofullerenes with chiral fragments.

Tulyabaev AR, Tuktarov AR, Khalilov LM.
MRC 2014 52, 3

Biophysical aspects of cyclodextrin interaction with paraoxon.

Soni SD, Bhonsle JB, Garcia GE.
MRC 2014 
Solution Structure of a G-quadruplex Bound to the Bisquinolinium Compound Phen-DC3.

Chung WJ, Heddi B, Hamon F, Teulade-Fichou MP, Phan AT.

Structure elucidation and NMR assignments of two unusual xanthones from Lomatogonium carinthiacum (Wulf) Reichb.

Wang Q, Bao B, Chen Y.

Structural elucidation and NMR assignments of two new pyrrolosesquiterpenes from Streptomyces sp. Hd7-21.

Liu DZ, Liang BW.

Automatic assignment of 1H-NMR spectra of small molecules.

Cobas C, Seoane F, Vaz E, Bernstein MA, Dominguez S, Pérez M, Sýkora S.

Tuesday, February 4, 2014

1 Mega-dalton and beyond ...

This week I'll take a look at a fascinating paper published in Angew. Chem. towards the end of 2013.  The title is "NMR spectroscopy of soluble protein complexes at one mega-dalton and beyond" by Mainz, Religa, Sprangers, Linser, Kay and Reif.

DOI: 10.1002/anie.201301215

Why should we care about protein complexes with a molecular mass greater than 1 mega-dalton?  Many of the most important biological processes in human health are mediated by large protein complexes.  To make matters worse, many of the most powerful tools available to chemists and biochemists, such as NMR, are not suitable for such systems.  What are the challenges in applying NMR spectroscopy to such large complexes?  In traditional protein NMR (aka solution state NMR) there are two issues: #1) There are too many signals in large complexes.  The resulting overlap makes it difficult to assign resonances and interpret data; #2) As the molecular mass increases, the spin-spin relaxation rate constant, R2 (= 1/T2) increases.  The resulting broad lines diminish sensitivity and resolution.  I'll note that many of the most important developments in NMR methodologies over the past 15 years have focused on addressing these limitations.  Examples include TROSY (along with perdeuteration) which fosters backbone resonance assignment of proteins with molecular mass of ~ 80 kDa and methyl-based labeling and methyl-TROSY experiments for side chain dynamics of very large systems (> 500 kDa).

In contrast to solution state NMR, for immobilized rigid solids spun rapidly at the "magic angle", the line width of resonances do not depend on molecular mass.  No matter how big the molecule, it is possible to acquire spectra with narrow lines (line width ~ 50 Hz) as long as the magic angle spinning (MAS) rate is greater than the anisotropic interactions that broaden lines in solids (such as dipolar coupling).  Fortunately, there has been impressive technical developments to miniaturize rotors and maximize spin rates.  The problem is that MAS solid state NMR (ssNMR) requires rigid solids, usually meaning crystals of protein complexes.

The authors have developed a technique that they call FROSTY MAS to take advantage of the fact that for solids the line width is not a function of molecular mass, while avoiding the inconvenience of working with solid samples.  In FROSTY MAS ~40 uL of ~3 mM protein (40x10^-6 * 3x10^-3 * 1x10^6 = .12 g!) is dissolved in a buffer with 30-40% glycerol and loaded into a 4 mm rotor.  The protein is fully deuterated at non-exchangeable sites and only ~20% protonated at exchangeable sites.  Also, there is Cu(II)-EDTA in the solution.  This mixture is loaded into a solids probe and spun at 22 kHz.  Under these conditions rotational reorientation is impeded and the molecule behaves just as if it were a rigid solid lattice, allowing the authors to get narrow lines regardless of the protein molecular mass!  The objective of this paper is to demonstrate that the FROSTY MAS technique can be used to acquire 1H-detected backbone-based ssNMR experiments for resonance assignments of large protein complexes.

The protein that Mainz et al. apply their novel technique to is the 20S proteasome with 11S activation lids.  The 20S proteasome is a multi-subunit complex consisting of 4 heptameric rings.  This protein plays a vital role in maintaining cellular function via selective degradation of proteins.  Figure 1 explains the modular architecture of this protein (along with the molecular mass and rotational correlation time of each complex).

One trick the authors use to reduce the number of signals is that only the alpha subunit is isotopically enriched.  So overall, their spectrum will have as many signals as a 26 kDa protein (233 residues), even though it tumbles like a 1.1 MDa complex!

What are the authors results?  First, they record a proton-detected MAS spectrum for three complexes: the double heptameric ring (a7a7, 360 kDa), the full 20S proteasome (a7b7b7a7, 670 kDa) and the 20S-11S complex (1.1 MDa).  Figure 3 shows these results.  

The y-axis of these plots are normalized to the concentration of alpha subunit in the samples.  The observation is that the signal increases with molecular mass.  The authors interpretation is that the sensitivity increases due to "the reduced rotational mobility of the larger assemblies in the sedimented state."  In other words, the larger complex is more solid-like so the ssNMR tricks work better.  An alternative explanation that the authors address is that chemical exchange is responsible for the difference in signal intensity.  One could imagine that the a7a7 or a7b7b7a7 samples are in slow or intermediate exchange between two conformations and the addition of the 11S cap stabilized one state.  The traditional tools to address chemical exchange, at least for small molecules, are temperature and field.  The authors do not use these tools here.  To be honest, I do not really follow their argument (which takes ~1 paragraph and jumps from CP to TROSY), but at the end the authors dismiss the possibility that  dynamics on the us-ms or ns-us timescale could be responsible for the sensitivity increase.  

The other major result is the backbone resonance assignment of the alpha subunit of the 1.1 MDa complex.  Kay and co-workers have assigned the single ring a7 complex (180 kDa) in solution.  Supplemental figure S3 overlays the 1H-15N TROSY of this molecule (red) with the FROSTY-MAS 1H-15N correlation spectrum of the 1.1 MDa complex.  

This figure certainly highlights the impressive sensitivity and resolution of the FROSTY-MAS experiment.  The authors also record hCAhNH and hCOhNH (ssNMR equivalent of the HNCA and HNCO) of the 1.1 MDa complex.  These experiments, in combination with the assignments from the solution state, enable backbone resonance assignment of 108 or 227 non-proline amino acids in the alpha subunit.  The less optimistic description is that 119 residues are not assigned.  Of course, Kay and co-workers could not assign (some of) these residues in the solution state either, because of ms-us timescale dynamics.  At any rate, using the assignments they have, the authors can map the interface between the 11S activator and the alpha subunit using chemical shift perturbations.  Also they can use a program like TALOS+ to assess the secondary structure from the Ca chemical shift.  

Overall, this paper is a very exciting demonstration of NMR spectroscopy on protein complexes that are so large that it would have been unthinkable to try to study a few years ago.  My imagination could run wild dreaming up uses for this technique.  One example is the crowded cellular environment.  I am a bit concerned about the mass and solubility requirements for this technique.  It is not cheap to make > 100 g of triple labeled protein.  Also, as I understand it, any aggregation or amorphous solids in the sample will undermine FROSTY-MAS.  These concerns are minor, though.  This paper is outstanding and paradigm shifting!  For very large protein complexes we could see solid state NMR surpass solution in the very near future, particular when taken in combination with other emerging solid techniques, such as DNP. 

Friday, January 24, 2014

NMR Thermometry Part 2

Yesterday I wrote a part 1 of a blog post regarding a Nature paper from October 2013.  You might want to check out that post before reading this one.

These two posts review/critique the paper "Thermal maps of gases in heterogeneous reactions" by Jarenwattananon et al.

My post yesterday was an attempt to review the publication.  I tried to minimize my comments and let the authors speak for themselves.  Today I plan to air my grievances and concerns about this paper.  

Before I begin I want to note that this paper got tons of press.  For example ..,229E6,E1MX8G,7GOMF,1

With so much attention, I'm sure my puny critiques will not be too rough for Jarenwattananon and co-workers.  I will divide them into three categories: accuracy, precision and sources of error.

#1) Accuracy.

In the body of the paper the authors state "The disagreement between NMR-derived temperatures and fibre-optic sensor measurements was at most 4%."  In the abstract they say "measurement error [is] less than four per cent of the absolute temperature."  I feel that it a bit misleading use agreement with external temperature sensors as a metric of accuracy.

Drill down into the paper and really ask yourself "what is the limit of accuracy in the temperature measurement?"  It has to be how accurately you can measure line widths of the analyte.  For example, Fig 1c shows data and Lorentzian fit for propylene in temperature calibration experiment.

Look carefully and tell me, what is the smallest line width difference you think that you can assess on such a spectrum?  Could you distinguish two spectra with line widths that differ by 1 Hz, 5 Hz or 10 Hz?    By inverting the linear equation (I'll use calibration curve for PtNP) , it is possible to calculate how much the temperature changes if line width changes by 1, 5 or 10 Hz.

T =  1 Hz / 0.16 Hz K^-1 = 6.25 K
T =  5 Hz / 0.16 Hz K^-1 = 31.25 K
T = 10 Hz / 0.16 Hz K^-1 = 62.5 K

4% of 400 K is 16 K, so the authors seem to acknowledge an accuracy of line width measurement of about 3 Hz.  I question if they can really measure the line width so accurately.  If the error is closer to +/- 25 K, then their false color thermal maps, particularly on the microreactor in Fig. 4b, could be quite misleading.

#2) Precision

In the caption for Fig. 1 and 3, the authors state that "temperature calibrations were performed for over 30 different systems." and "thermal maps were generated for more than 15 systems."  How much do the results vary from system-to-system?  Are these variations an indication of the variation in each reactor or the precision of the measurement.  If you repeat the calibration or mapping experiment several times how much variation would you see?

#3) Sources of error

I think of this experiment as almost an anti-DOSY.  In this experiment, the NMR signal in the presence of a gradient is sharpened not attenuated by molecular motion.  I surmise that this experiment works because gas molecules at elevated temperatures diffuse fast enough average gradients.  The problem as I see it is that this experiment only works if everyone agrees that the only factor that impacts the line widths is molecular motion.  You could fool yourself and think you see a cool spot if regions of the sample have any reason other than the gradient to have broad lines.  Some examples that spring to mind with heterogeneous catalysts is local concentration of paramagnetic substances. 

A related issue that troubles me is that the slope of the calibration curve (deltaF vs. T) is different for the two catalysts (PtNP and Pd-MOF).  I don't understand why.  It seems like if gradient-induced line width is narrowed by motional averaging (which is related to T) the specific catalysts should not matter.  Why is deltaF equal to -87 Hz at 400 K and G equals 0.05 G cm^-1 for PtNP and -79 Hz for Pd-MOF.  Either the material impacts the line width (which is clearly what the authors think) or these values represent errors in line width measurement.


In the end, I really love this paper.  It really made me think about stuff I don't get to think about too much line mean free path and the Maxwell distribution.  I get persnickety about a few issues, but you shouldn't let me distract you from the unprecedented view into reactor energetics this new NMR thermometry technique offers.    

Thursday, January 23, 2014

NMR thermometry

The paper for this week was published back in late October in Nature.  I'm just getting to it now though,  because a) I'm always a bit behind and b) the title "Thermal maps of gases in heterogeneous reactions" does not alert the reader that the content of this paper is highly relevant to anyone who wishes to be fluent in contemporary NMR research.  The full citation is

"Thermal maps of gases in heterogeneous reactions"


Jarenwattananon, Gloggler, Otto, Melkonian, Morris, Burt, Yaghi and Bouchard

Nature 2013 502, 537

This paper describes a novel NMR thermometry technique to measure gas temperatures at gas-solid interfaces in heterogeneous catalysts.  For engineers who optimize reactor design, temperature gradients on catalyst beds contain vital information on reaction energetics (so I am told).  The key insight of the authors is that in the presence of a weak magnetic field gradient (<< 1 G cm^-1) motional averaging will result in an inverse relationship between line width of a given peak and temperature of the system.  Figure 1a provides an excellent pictorial description of this technique.

To demonstrate the feasibility of NMR thermometry, the authors design a simple calibration experiment using a 10 mm NMR tube with catalyst-loaded glass wool (more on their catalysts later) and an analyte of propylene gas flowing at 15 cc min^-1, 40 PSI.  A 1D 1H spin echo spectrum is recorded with gradient applied during acquisition on a 400 MHz NMR (with microimaging capabilities) and the probe temperature set from 303 to 413 K in 10 K steps.  A sum of Lorentzians is fit to the olefin region of the propylene spectrum to get line widths.  Figure 1b shows linear fit of a plot of the change in linewidth relative to 303 K (deltaF) versus temperature (T) for three different gradient strength.

In the absence of a gradient, the slope of deltaF versus T is negative but small.  For a gradient strength of 0.1 G cm^-1, the slope is -0.13 Hz K^-1.  A stronger gradient results in a larger slope.

The authors settle on 0.005 G cm^-1 for gradient strength for their NMR thermometry setup.  They measure deltaF vs. T for two catalysts: Pt nanoparticles (PtNP) and Pd metal-organic frameworks (Pd-MOF).  Least squares fit results in a slope and intercept of -0.16 Hz K^-1 and 151 Hz and -0.10 Hz K^-1 and 119 Hz for PtNP and Pd-MOF, respectively.  Now the authors have the tools in place to measure T by NMR.  Simply measure the line width (of propylene olefin peaks) in 1D 1H spectrum with a gradient of 0.05 G cm^-1 during acquisition and use the appropriate linear equation to calculate temperature.

Having convincing demonstrated feasibility, the authors move to an application: thermal maps of lab-scale demo reactors with each catalysts.  In this experiment, propylene and hydrogen gas (actually para-hydrogen) are flowed through the reactor at 15 cc min^-1, 40 PSI and catalysis (hydrogenation) takes place.  The microimaging experiment (which takes ~30 min) divides the reactor into voxels and in each voxel the spin echo/gradient experiment is performed.  Line widths and, subsequently, temperature is determined for each 0.73 x 0.73 mm pixel in the reactor.  Figure 3 shows false color image of axial, coronal and sagittal views of the reactors.

Significant variations in the temperature of the catalyst bed is observed.  There are spots with T > 600 K and other spots with T < 400 K!  To validate these results, the authors carefully place a fiber optic temperature sensor at 3 spots in the demo reactor (you can see where in the coronal view of PtNP and sagittal view of Pd-MOF reactors).  The sensor agrees well with NMR thermometry-derived T.  The error is at most 4%.

Finally, the authors demonstrate NMR thermometry on a 1 mm microreactor with catalyst supported on silica gel.  Para-hydrogen preheat to 418 K is flowed into the reactor.  I assume that there is also propylene.  I have no clue what the flow and pressure is because the authors do not go out of their way to bore us with any details.  The temperature calibration experiment results in a slope of -0.2 Hz K^-1.  No mention of the intercept.  Figure 4 show a false color image thermal map from the microimaging experiment.

Once again, NMR thermometry reveals significant temperature variations in the reactor from 30 K higher than gas T at the inlet to 30 K lower at the outlet.

This is an amazing paper!  It is easy to understand why it was published in Nature.  The thermal maps in Fig. 2 and 4 are incredible.  I am no expert, but  don't see any other way to measure these types of temperature gradients on this scale other than NMR thermometry.  In Fig. 4 for instance, there is a gradient of ~60 degrees over a space of ~2.5 mm (which is less than 1/10 of 1 inch).


I'm going to make this a two-part blog and return tomorrow and sharpen my critique up a little bit.  See you then.


Thursday, January 9, 2014

Wrapping up 2013

There were a lot of papers that I read last year and really liked.  I would like to write a full critique, but I just don't have time.  So here is my twitter critique (<150 words - I know that twitter uses characters, but give me a break.)

The quiet renaissance of protein nuclear magnetic resonance


Paul Barrett and a cast of thousands

Super well-written review.  A call to arms to NMR spectroscopists to embrace NMR as a broad problem-solving tool rather than machine that generates PDB files.

Mycalol: A natural lipid with promising cytotoxic properties against human anaplastic thyroid carcinoma cells


Adele Cutignano and co-workers;jsessionid=E7C1B2F402EF5A4BA96E06EFFEF70D1F.f04t03

A great natural products structure elucidation paper.  This paper is what really inspired me to start this blog.  The authors isolated a lipid from a sponge they found in Antarctica.  The molecule has five stereocenters and it would have been a pain in the ass to assess stereochemistry using NOE and J coupling.  The authors use CD and Mosher's method and a lot of clever logic.  A+

Characterization of Cyclopentyllithium and Cyclopentyllithium Tetrahydrofuran Complex


Su, Hopson and Williard

The first of three JACs papers published by these authors this fall.  Good grief.  I won't get three JACS papers in a lifetime.  These guys got three during the football season!  This one is probably my favorite for the cool use of DOSY to explore the equilibrium between a hexameric and tetrametric molecule.   

The influence of electronic modifications on rotational barriers of bis-NHC-complexes as observed by dynamic NMR spectroscopy


Kolmer, Kaltschnee, Schmidts, Peeck, Plenio and Thiele (so many Germans and no umlauts!)

A great physical organic chemistry paper regarding Grubbs catalysts.  Quantitative dynamics to measure rotational barriers and a clear relationship between redox properties and rotational barrier.  Nice work.

Direct Measurements of the Mn(II) hydration state in metal complexes and metalloproteins through 17O NMR linewidths


Gale, Zhu and Caravan

NMR tricks to assess the hydration state of metal complexes.  Relaxivity measurements.  Sign me up. 

Xenon-based Molecular Sensors

This weeks paper is a hot-off-the-press JACs article by Garimella et al.  The full title is

Hyperpolarized Xenon-Based Molecular Sensors for Label-Free Detection of analytes.


Garimella PD, Meldrum T, Witus LS, Smith M, Bajaj VS, Wemmer DE, Francis MB, Pines A.
The full citation is

A few months ago I reviewed a very nice paper by Perrone et al. regarding NMR-based sensors (see  This weeks paper describes an alternative approach to designing an NMR-based sensor.  Garimella et al. design a sensor with two binding sites.  One site will bind a specific analyte, in this case the dye Rhodamine 6G.  The other site will bind xenon gas molecules dissolved in solution.  It turns out that xenon NMR is so sensitive that subtle changes on the other end of the sensor, such as the binding of a ligand, alter the chemical shift.  Below it the TOC graphic to explain the concept visually.


What do the author's actually do?

They begin by creating a peptide receptor library with 1.6e5 (=20^4) molecules based on the sequence KXXPGXXGWKKG.  Their hope is that some of these molecules (~2% or so - which is 3,200) will bind with a dye.   These peptides are bound to polystyrene beads at the C-terminus and pyrene at the N-terminus.  Since the peptides are attached to beads, the authors incubate the bead library with 10 uM dye for 1 hour, wash away the dye and manually sort the colored beads.  (I am glad I don't have that job.)  They screen the bead library multiple times and sequence the hits by mass spectrometry.  I am sure that this part is pretty clever, but the details are a bit lost on me.  In the end, their consensus sequence to bind Rhodamine 6G is H2N-KDDPGDEDWKKG-CO2H, which they call the "D-peptide."  The make another peptide as a control with the sequence H2N-KNNPGNQGWKKG-CO2H.  They call this peptide the "N-peptide."  The figure below shows visual confirmation that the D-peptides binds with Rhodamine 6G using the bead incubation assay, whereas the N-peptides does not show any color change.  So are we the audience to assume that the N-peptide does not bind the dye?  At this stage, I think the answer is yes. 


Garimella et al. can now move away from the beads and focus on the peptides.  They do some smart controls like replacing the pyrene with the Xenon binding cryptophane cage at the N-terminus to confirm that the dye binds to the peptide, not the pyrene.  They also confirm specificity by trying many other dyes, none of which bind with the D-peptide (no word about the N-peptide, though).  

Now we can get into some spectroscopy.  The authors use NOESY to confirm the interaction between the dye and D-peptide.  Their sample is 250 uM dye and 200 uM D-peptide-cage.  They also record a NOESY of 250 uM dye and 200 uM N-peptide-cage.  Here is what the authors report:

"The spectra of both the D- and N-peptides in the presence of dye revealed cross peaks in the region corresponding the dye-peptide interactions.  However, there were many more cross peaks in the D-peptide-cage sample, and they were more intense than those in the N-peptide-cage sample."

and then a bit later

"The NOE data .. verifie(s) that there was a difference in interaction of the dye with the D- and N-peptides, confirming our visual evidence that the library produced a receptor for the Rhodamine 6G analyte."  
So much for a negative control!  Still you have to give the authors a lot of credit for turning a bug into a feature.  (I am stealing that phrase from my friend Todd, who used it to describe a research projects around here.  It seems to me that the ability to turn a bug into a feature is a key trait in good science.)  So the N-peptide binds Rhodamine 6G, albeit with less affinity than the D-peptide.  As a final note on this topic, it seems to me that there is something funny going on with the interactions between the dye and peptide.  I spent some time staring at the NOESY spectra in the SI and I can't make heads or tails of this interaction. 

On to the Xenon-based detection - The Pines lab has developed a really cool system to deliver optically hyperpolarized xenon gas into their NMR samples.  The net result is a HUGE signal.  In the introduction to this paper the authors say that the NMR signal has the "strength compatible to those of water in conventional experiments."  I am assuming that they only need one scan!

At any rate, the authors make ten NMR samples, five for the D-peptide-cage, five for the N-peptide-cage each with increasing dye concentration from 0 to 1000 uM in steps of 250 uM.  The peptide concentration equals 200 uM.  Let's first consider the Xe NMR spectrum for the peptide-cage samples with no dye.  There are three peaks.  One for hyperpolarized Xe bound to the cage at ~60 ppm.  There is a sample for aqueous Xe (some the gas pumped into the solution dissolves in the solvent like CO2 in soda pop) at ~200 ppm.  There is also so undissolved Xe gas signal, which is set to 0 ppm.  (Since these signals are in slow exchange, I guess the dissolution process is slow on the NMR time scale.)  The gaseous signal is used as a reference and set to zero ppm in all spectra.  What I find strange is that the exact chemical shift of the aqueous Xe is at ~190.75 for the D-peptide and 191.25 for the N-peptide.  This is not a good quality for a sensor to possess.  I think that you would want any extra unbound sensor to be impervious to other conditions in the solution.  Is Xe sensing the pH of the solution (presumably the pKa of the D- and N- peptide is different)?  The authors did warn us that Xe NMR was sensitive.  The exact chemical shift of the Xe bound to cage equals ~60.5 ppm for the D-peptide and 62.25 ppm for the N-peptide.  I'll say it again - The authors did warn us that Xe NMR was sensitive.

Let's first consider the D-peptide.  When dye is added to the solution both peaks shift.  The aqueous Xe moves upfield and the Xe-cage moves downfield.  I think it is strange that the aqueous Xe shifts, but it is what it is.  The Xe-cage moves quite a bit more than the aqueous, Xe by the way.  Now let's consider the N-peptide.  As the dye concentration increases, the Xe-cage peak move upon binding with the N-peptide, albeit less than with the D-peptide.  The authors advocate using the difference between the peaks as a readout of the assay.  Using this metric, the Xe peaks move 0.78 and 0.33 ppm for the D-peptide-cage and N-peptide-cage upon binding 1 mM dye.  See figure below ...  

I am going to criticize this paper a bit, so I'll issue my usual caveat: I am a nobody doing LN2 fills and teaching 1st year graduate students how to acquire 1D 1H spectra, whereas the authors of this paper are real scientists doing the hard, creative work of producing scientific knowledge.  My purpose in starting this blog is not to trash people's work so that I feel better about my life.  I wanted to force myself (on a very public forum) to critique great science in hope of improving my science.  So here is my critique in one sentence: the negative control is not so negative.  Traditionally, in a paper like this one, you would have one positive and one negative control, proving that you get a signal when the analyte is present and no signal when the wrong analyte present.  In this paper the authors see a delta delta of 0.78 ppm for a carefully chosen strong binder and a delta delta of 0.33 ppm for a weaker binder.  If they could make a non-binder would the delta delta equal 0 ppm?  What would they see if they tried another dye molecule? 

Overall, I give the authors a lot credit for using a SELEX type procedure to hunt out a binder.  I kind of glossed over this point earlier to get to the spectroscopy, but it was a substantial effort to find a needle in a stack with 20^4 pieces of hay.  Clearly, this paper is a starting point.  The authors set out to show that their sensor-cage-Xe trick would is feasible.  I think they succeeded.  I wonder if their problem isn't going to be that Xe NMR is just too sensitive, though.