The authors are grateful to Michaela Zamponi at the J&#252;lich Centre for Neutron Science at the Heinz Maier-Leibnitz Zentrum, Garching, Germany, for part of the neutron scattering experiments conducted on the instrument SPHERES. This work has benefited from the activities of the Deuteration Laboratory (DLAB) consortium funded by the European Union under Contracts HPRI-2001-50065 and RII3-CT-2003-505925, and from UK Engineering and Physical Sciences Research Council (EPSRC)-funded activity within the Institut Laue Langevin EMBL DLAB under Grants GR/R99393/01 and EP/C015452/1. Support by the European Commission under the 7th Framework Programme through the Key Action: Strengthening the European Research Area, Research Infrastructures is acknowledged [Contract 226507 (NMI3)]. Kevin Pounot and Christian Beck thank the Federal Ministry of Education and Research (BMBF, grant number 05K19VTB) for funding of their postdoctoral fellowships.

1. Prepare the deuterated buffer for proteins in the liquid state
<ol>
	<li>Dissolve all components of the buffer in pure D2O.</li>
	<li>If the pH electrode was calibrated in H2O, adjust the pD according to the formula pD = pH + 0.4 using NaOD or DCl34. 
	NOTE: The use of D2O instead of H2O might affect protein solubility and the buffer conditions might need to be adapted, (e.g., by a slight change in salt concentration).</li>
</ol>
2. Prepare the H2O-hydrated powders of perdeuterated protein
<ol>
	<li>Prepare the sample holder.
	<ol>
		<li>Thoroughly clean a flat aluminum sample holder with its indium wire seal and screws with water and ethanol and let it dry. 
		NOTE: A flat sample holder is used such that the powder can be homogenously distributed over the surface. The amount of powder should be sufficient such that it can be maintained between the walls and does not fall when the sample holder is placed vertically.</li>
		<li>Weigh the different parts of the sample holder-bottom, lid, and indium wire-separately on a precision balance.</li>
		<li>Place the 1 mm indium wire seal in the groove of the bottom part of the sample holder, leaving a small overlap where the two ends join (Figure 2A).</li>
		<li>Place an appropriate amount of lyophilized protein (typically ~100 mg of protein) such that it fills the inner surface of the bottom part of the sample holder.</li>
	</ol>
	</li>
	<li>Hydrate the protein powder.
	<ol>
		<li>Place the sample holder in a desiccator with a Petri dish containing P2O5 powder for 24 h to completely dry the protein powder35 (Figure 2B). Weigh the dry bottom part of the sample holder containing the indium seal and the dry powder to obtain mdry. 
		CAUTION: P2O5 powder is very corrosive.</li>
		<li>Remove the P2O5 from the desiccator and put a Petri dish with D2O inside. Control the mass of the powder regularly to check the hydration level h = mhyd / mdry where mhyd and mdry are the mass of the hydrated powder and dry powder, respectively. 
		NOTE: For highly hydrophobic proteins such as insulin, it might be necessary to increase the temperature inside the desiccator to get a higher vapor pressure and reach the desired hydration level h.</li>
		<li>Repeat steps 2.2.1 and 2.2.2 at least three times to properly convert all exchangeable hydrogens to deuterons. 
		NOTE: Alternatively, cycles of freeze-drying and dissolution in pure D2O might be used for better H/D exchange provided that the protein is not affected by it.</li>
		<li>Hydrate the powder to slightly above the desired level, let the bottom part of the sample holder with the indium wire and hydrated powder remain on the precision balance, and wait for the mass to decrease slowly to the desired value to get the target h (typically 0.2-0.4 if a medium sized globular protein is to be covered by one complete hydration layer).</li>
		<li>Quickly put the lid on the bottom part and close the sample holder first with four screws to stop the vapor exchange (Supplemental Figure S3A).</li>
		<li>Place and tighten all remaining screws until no gap is visible between the bottom part and the lid (Supplemental Figure S3B).</li>
		<li>Weigh the sealed sample holder to check for any potential hydration loss via leaks after the neutron experiment.</li>
	</ol>
	</li>
</ol>
3. Perform the incoherent neutron scattering experiment
<ol>
	<li>Discuss and double-check the configuration of the instrument needed for the experiment with the local contact some weeks before the assigned beamtime.</li>
	<li>Prepare the liquid state sample.
	<ol>
		<li>Dissolve the protein in the deuterated buffer.</li>
		<li>Determine the appropriate volume of liquid to be put in the sample holder using water (ensure there is no overflow when the sample holder is closed; Figure 2C). 
		NOTE: The following steps (3.3 and 3.4) describe an experiment conducted on the NBS spectrometer IN16B at the ILL8,9, using a cryofurnace as a sample environment. The instrument control system will change from one instrument to the other, but the working principles remain the same.</li>
	</ol>
	</li>
	<li>Insert the sample.
	<ol>
		<li>Thoroughly dry the sample stick (Figure 2D), and remove the previous sample, if any, after checking that the ionizing radiation dose is lower than 100 &#181;Sv/h before handling any material (at the ILL).</li>
		<li>Place the sample, check for proper centering relative to the beam center (Supplemental Figure S4), and insert the sample stick in the cryofurnace (Figure 2D). Turn on the vacuum pump to reach less than 10-3 bar, and flush out the air inside the cryofurnace by repeating the following three times: fill the cryofurnace with helium gas until atmospheric pressure is reached, and remove the gas again using the vacuum pump. 
		NOTE: In case of a flat sample holder, the sample holder must be oriented at a 45&#176; angle relative to the incoming beam. The useful momentum transfer range could be reduced due to absorption and scattering by the cell. A strong neutron absorber such as cadmium can be used to mask certain parts of the sample holder (e.g., screws, thick parts).</li>
		<li>Introduce some helium gas in the cryofurnace such that the pressure is ~0.05 bar.</li>
	</ol>
	</li>
	<li>Acquire data (e.g., using NOMAD on IN16B at the ILL, it is assumed that the user prefers a temperature of 200 K before acquiring a quasielastic neutron spectrum (QENS) spectrum, then E/IFWS during a temperature ramp to 310 K at 0.5 K per min and finally a QENS at 310 K).
	<ol>
		<li>Using NOMAD, in the execution tab, drag and drop a FurnaceCryostat controller in the Launch Pad. Set the temperature to 200 K. Use the fast mode and a timeout of 30 min such that the temperature has time to stabilize. Click on the rotating arrows icon to run it in the background such that data can be acquired during the temperature decrease.</li>
		<li>Drag and drop the IN16DopplerSettings controller, set the speed profile to Accurate velocity set by Max &#916;E, a value of 0.00 &#181;eV and 128 channels to obtain an EFWS configuration.</li>
		<li>Drag and drop a Count controller, fill the Subtitle field with a name that allows easy identification of the data, and set 60 repetitions of 30 s scans (Supplemental Figure S5A).</li>
		<li>Drag and drop an IN16DopplerSettings controller, set the speed profile to Sine set by Speed with a value of 4.5 m/s and 2,048 channels to obtain a QENS configuration.</li>
		<li>Drag and drop a Count controller with 4 repetitions of 30 min scans (Supplemental Figure S5B).</li>
		<li>For the temperature ramp, drag and drop a FurnaceCryostat controller, set the temperature to 310 K, set Ramp to SetPoint with &#916; = 0.05 K and 6 s. Use a time out of 220 min (Supplemental Figure S6A).</li>
		<li>Use a for loop with 65 repetitions. Inside, insert an IN16DopplerSettings controller as in step 3.4.2, followed by a single count of 30 s. Subsequently, insert IN16DopplerSettings, as described previously but using an energy offset of 1.5 &#181;eV and 1,024 channels followed by a single count of 3 min (Supplemental Figure S6B).</li>
		<li>To acquire the last QENS at 310 K, drag and drop IN16DopplerSettings and Count controllers configured as described in steps 3.4.4 and 3.4.5, respectively.</li>
		<li>Press the start button (right triangle on the bottom of the window) to run the script. 
		NOTE: Every experiment will require the acquisition of calibration data; that is, the empty cell for subtraction or absorption corrections, the buffer alone at the different temperatures used to model the background, and a measurement of vanadium (or equivalently, the sample at a temperature of 10 K or lower) to obtain the resolution function of the instrument.</li>
	</ol>
	</li>
</ol>
4. Data analysis - QENS
<ol>
	<li>Import the dataset using the &#39;IN16B_QENS.process()&#39; method in the Python software nPDyn v3.x36 
	&#62;&#62;&#62;&#62; from nPDyn.dataParsers import IN16B_QENS 
	 
	&#62;&#62;&#62; sample = IN16B_QENS( 
	...&#60;path to data files&#62; 
	... [detGroup=&#60;integer or detector grouping file in XML 
	...format&#62;] 
	... ).process() 
	 
	&#62;&#62;&#62; sample = sample.get_q_range(0.3, 1.8)</li>
	<li>Perform data corrections (optional) with the following commands (see the documentation of nPDyn for more information, Figure 3): 
	#it is assumed that data for empty cell, vanadium, and buffer 
	# were imported already in dataset called &#39;empty_cell&#39;, &#39;vanadium&#39;, 
	# and &#39;buffer&#39;, respectively. 
	 
	# for empty cell subtraction with a scaling factor 
	# (errors are propagated automatically) 
	&#62;&#62;&#62; sample = sample - 0.95 * empty_cell 
	 
	# for correction using Paalman-Ping coefficient 
	# (mutually exclusive with the example above) 
	&#62;&#62;&#62; sample = sample.absorptionCorrection(empty_cell) 
	 
	# for normalization 
	&#62;&#62;&#62; sample = sample.normalize(vanadium) 
	 
	# for binning along observable axis 
	# observable is the aggregation time here 
	&#62;&#62;&#62; sample = sample.bin(3, axis=0)</li>
	<li>Fit the calibration data. The dataset-samples, empty cell, deuterated buffer (if needed), and vanadium-can be fitted using built-in models or a user-defined model (see nPDyn documentation): 
	&#62;&#62;&#62; from nPDyn.models.builtins import ( 
	... modelPVoigt, 
	... modelWater, 
	...modelCalibratedD2O, 
	... ) 
	 
	# builtin models use a column vector of the momentum 
	# transfer q values 
	&#62;&#62;&#62; q = vanadium.q[:, None] 
	 
	# the vanadium is fitted using a pseudo-Voigt profile 
	&#62;&#62;&#62; vanadium.fit(modelPVoigt(q))</li>
	<li>Use the built-in model for hydration water called &#39;modelWater&#39;. This model reads as shown by Eq (4)17 
	<img alt="Equation 4" src="/files/ftp_upload/63664/63664eq04.jpg" style="margin: auto;" /> (4) 
	Where a0, ar, and at are scalars accounting for the relative contribution of elastic signal, rotational motions, and translational motions, respectively; j1(qd) is the lth order spherical Bessel function, with q being the momentum transfer; d the O-H distance in the water molecule;&#160;&#948;(&#969;) is the Dirac delta, which is multiplied by the EISF here; N is the highest order of the spherical Bessel function used (typically ~5); <img alt="Equation 5" src="/files/ftp_upload/63664/63664eq05.jpg" style="margin: auto;" /> and <img alt="Equation 11" src="/files/ftp_upload/63664/63664eq11.jpg" style="margin: auto;" /> are the Lorentzian rotational and translational motions, respectively; b(q) is a flat background term. The spherical Bessel functions give the relative contribution of each angular momentum state of the water molecules, and the number N is determined based on the momentum transfer q-range. In the case of a typical NBS spectrometer, the terms up to N = 4 almost entirely explain the signal (Supplemental Figure S7). 
	# here, equation 2 is used for hydration water 
	# convolution with resolution function and addition of 
	# D2O background is done automatically with the 
	# provided arguments 
	&#62;&#62;&#62; sample.fit(modelWater(q), 
	... res=vanadium, 
	... bkgd=buffer, 
	... volume_fraction_bkgd=0.95 
	... ) 
	NOTE: The contributions of rotational and translational motions should be convoluted to be perfectly rigorous. The success of an additive model is to be attributed to the presence of distinct populations of water on the protein surface and the limited energy range accessible.</li>
	<li>Use the following to plot the data (Figure 4): 
	&#62;&#62;&#62; from nPDyn.plot import plot 
	&#62;&#62;&#62; plot(sample)</li>
</ol>
5. Data analysis - temperature ramp, elastic fixed-window scans (EFWS)
<ol>
	<li>Use a procedure similar to section 4 to normalize the temperature ramp data by the signal at the lowest temperature (typically 10 K): 
	&#62;&#62;&#62; from nPDyn.dataParsers import IN16B_FWS 
	 
	&#62;&#62;&#62; sample = IN16B_FWS( 
	... &#60;path to data files&#62;, 
	... detGroup=[detGroup=&#60;integer or detector grouping file in XML format&#62;] 
	... ).process() 
	 
	# normalization with the 5 first points on the observable 
	# axis, which correspond to the temperature 
	&#62;&#62;&#62; sample /= sample[:5].mean(0) 
	 
	# the momentum transfer q range used here is smaller 
	# as the model used is valid for low q only 
	&#62;&#62;&#62; sample = sample.get_q_range(0.2, 0.8)</li>
	<li>Use a simple Gaussian model to start, the width of which is given by the so-called mean squared displacement (MSD). Build and fit the model using the following commands: 
	&#62;&#62;&#62; import numpy as np 
	&#62;&#62;&#62; from nPDyn.models import Parameters, Model, Component 
	 
	# a is a scaling factor 
	&#62;&#62;&#62; params = Parameters( 
	... a={&#39;value&#39;: 1, &#39;bounds&#39;: (0, np.inf)}, 
	... msd={&#39;value&#39;: 1, &#39;bounds&#39;: (0, np.inf)} 
	... ) 
	 
	&#62;&#62;&#62; model = Model(params) 
	&#62;&#62;&#62; model.addComponent(Component( 
	&#8230; &#39;gaussian&#39;, 
	&#8230; lambda x, a, msd: a * np.exp(-x ** 2 * msd / 6) 
	&#8230; )) 
	 
	&#62;&#62;&#62; sample.fit(model, x=sample.q[:, None]) 
	 
	&#62;&#62;&#62; plot(sample) 
	NOTE: The Gaussian approximation always holds for q2MSD &#60;&#60; 1, but wider momentum transfer range can be used for relative comparison between samples. More sophisticated models, which go beyond the Gaussian approximation, have been developed37,38,39.</li>
</ol>
6. Data analysis - elastic and inelastic fixed-window scans (E/IFWS)
<ol>
	<li>Similar to step 4, import the dataset but using the &#39;IN16B_FWS&#39; class: 
	&#62;&#62;&#62; from nPDyn.dataParsers import IN16B_FWS 
	 
	&#62;&#62;&#62; sample = IN16B_FWS( 
	...&#60;path to data files&#62; 
	... [detGroup=&#60;integer or detector grouping file in XML format&#62;] 
	... ).process() 
	 
	&#62;&#62;&#62; sample = sample.get_q_range(0.3, 1.8)</li>
	<li>Fit the calibration data and sample data.
	<ol>
		<li>Analyze the E/IFWS data using a generalized MSD40 or by considering them as coarse-QENS spectra (having only a few data points on the energy axis). When E/IFWS is viewed as coarse-QENS, models used for QENS are used to fit the whole E/IFWS dataset at once (global fit of energy transfers and momentum transfers). 
		NOTE: The latter solution-using models for QENS on E/IFWS data-is used here where the momentum transfer dependence of center-of-mass diffusion and protein internal dynamics are imposed.</li>
		<li>Model protein dynamics in liquids using the following Eq (5) (&#39;modelProteinJumpDiff&#39; in nPDyn): 
		<img alt="Equation 6" src="/files/ftp_upload/63664/63664eq06v2.jpg" style="margin: auto;" /> (5) 
		Where R(q,&#969;) is the resolution function;&#160;&#946; a scalar independent for each momentum transfer q; a0 is the elastic incoherent structure factor (EISF); <img alt="Equation 7" src="/files/ftp_upload/63664/63664eq07.jpg" style="margin: auto;" /> a Lorentzian accounting for center-of-mass diffusion with a width given by Eq (6); <img alt="Equation 12" src="/files/ftp_upload/63664/63664eq12.jpg" style="margin: auto;" /> is a Lorentzian that includes center-of-mass diffusion and a contribution following the jump-diffusion model14 accounting for internal dynamics (Eq (7); <img alt="Equation 8" src="/files/ftp_upload/63664/63664eq08.jpg" style="margin: auto;" /> being the fitted signal from D2O rescaled by its volume fraction in the sample. 
		&#947; = Dsq2&#160; (6) 
		Ds&#160;being the self-diffusion coefficient. 
		<img alt="Equation 9" src="/files/ftp_upload/63664/63664eq09.jpg" style="margin: auto;" /> (7) 
		Di&#160;being the apparent diffusion coefficient for internal dynamics and &#964; a relaxation time for diffusive motions. 
		&#62;&#62;&#62; from nPDyn.models.builtins import ( 
		... modelPVoigt, 
		... modelProteinJumpDiff, 
		...modelCalibratedD2O, 
		... ) 
		 
		# builtin models use a column vector of the momentum 
		# transfer q values 
		&#62;&#62;&#62; q = vanadium.q[:, None] 
		 
		# the vanadium is fitted using a pseudo-Voigt profile 
		&#62;&#62;&#62; vanadium.fit(modelPVoigt(q)) 
		 
		# for pure D2O, a model with calibrated linewidth 
		# for different temperatures is included in nPDyn 
		&#62;&#62;&#62; buffer.fit(modelCalibratedD2O(q, temp=363)) 
		 
		# here, equation 3 is used for liquid samples 
		# convolution with resolution function and addition of 
		# D2O background is done automatically with the# provided arguments 
		&#62;&#62;&#62; sample.fit(modelProteinJumpDiff(q), 
		... res=vanadium, 
		... bkgd=buffer, 
		... volume_fraction_bkgd=0.95 
		... )</li>
	</ol>
	</li>
	<li>Plot the fitted data using: 
	&#62;&#62;&#62; from nPDyn.plot import plot 
	&#62;&#62;&#62; plot(sample)</li>
</ol>

The authors have no conflicts of interest to disclose.

Neutron spectroscopy is the only method that allows probing the ensemble-averaged ps-ns dynamics of protein samples regardless of the size of the protein or the complexity of the solution when deuteration is used6. Specifically, by probing self-diffusion of protein assemblies in solution, the hydrodynamic size of such assemblies can be unambiguously determined. Nonetheless, the method is commonly limited by the low neutron flux, which implies long acquisition times and the requirement of high amou...

The neutron is a charge-less and massive particle that has been successfully used over the years to probe samples in various fields from fundamental physics to biology1. For biological applications, small-angle neutron scattering, inelastic neutron scattering, and neutron crystallography and reflectometry are extensively used2,3,4. Inelastic neutron scattering provides an ensemble-averaged measurement of the dynamics without requiring specific labeling per se, and a signal quality that does not depend on the size or the protein5.&#160;The measurement can be done using a highly complex environment for the protein under study that mimics the intracellular medium, such as a deuterated bacterial lysate or even in vivo3,6,7. Different experimental setups can be used to study the dynamics, namely i) time-of-flight-giving access to sub-ps-ps dynamics, ii) backscattering-giving access to ps-ns dynamics, and iii) spin-echo-giving access to dynamics from ns to hundreds of ns. Neutron backscattering makes use of the Bragg&#39;s law 2d sin&#952; = n&#955;, where d is the distance between planes in a crystal,&#160;&#952; the scattering angle, n the scattering order, and&#160;&#955; the wavelength. The use of crystals for backscattering toward the detectors allows for achieving a high resolution in energy, typically ~0.8 &#181;eV. To measure the energy exchange, either a Doppler drive carrying a crystal in backscattering is used to define and tune the incoming neutron wavelength8,9,10 (Figure 1), or a time-of-flight setup can be used at the cost of a decrease in energy resolution11.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63664/63664fig01.jpg" /> 
Figure 1: Sketch of a neutron backscattering spectrometer with a Doppler drive. The incoming beam hits the phase space transformation (PST) chopper42, which increases the flux at the sample position. It is then backscattered towards the sample by the Doppler drive, which selects an energy E1 (cyan arrow). The neutrons are then scattered by the sample (with different energies represented by the color of the arrows) and the analyzers, made of Si 111 crystals, will only backscatter neutrons with a specific energy E0 (red colored arrows here). Hence, the momentum transfer q is obtained from the detected position of the neutron on the detector array, and the energy transfer is obtained from the difference E1- E0. The time-of-flight expected for the neutron pulse produced by the PST is used to discard the signal from the neutrons scattered directly toward the detector tubes. Abbreviation: PST = phase space transformation. <a href="https://www.jove.com/files/ftp_upload/63664/63664fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
For backscattering spectroscopy, the main contribution to the signal from hydrogen proton-rich samples, such as proteins, comes from incoherent scattering, for which the scattering intensity Sinc(q, &#969;) is shown by Eq (1)12
<img alt="Equation 1" src="/files/ftp_upload/63664/63664eq01.jpg" style="margin: auto;" /> (1)
Where &#963;inc is the incoherent cross-section of the element considered, k&#39; is the norm of the scattered wavevector, k the norm of the incoming wavevector, q (= k - k&#39;) the momentum transfer, rj(t) the position vector of atom j at time t, and&#160;&#969; the frequency corresponding to the energy transfer between the incoming neutron and the system. The angular brackets denote the ensemble average. Hence, incoherent scattering probes the ensemble-averaged single-particle self-correlation of atom positions with time and gives the self-dynamics averaged over all atoms in the system and different time origins (ensemble average). The scattering function is the Fourier transform in time of the intermediate scattering function I(q, t), which can be viewed as the Fourier transform in space of the van Hove correlation function shown by Eq (2):
<img alt="Equation 2" src="/files/ftp_upload/63664/63664eq02.jpg" style="margin: auto;" /> (2)
Where &#961;(r,t) is the probability density of finding an atom at position r and time t13.
For a Fickian diffusion process, the self-diffusion function results (see Eq (3)) after a double Fourier transform in a scattering function consisting in a Lorentzian of line width given by &#947; = Dq2.
<img alt="Equation 10" src="/files/ftp_upload/63664/63664eq10.jpg" style="margin: auto;" /> (3)
More sophisticated models were developed and found useful such as the jump diffusion model by Singwi and Sj&#246;lander for ps-ns internal protein dynamics14 or the rotation model by Sears for hydration water15,16,17.
On the neutron backscattering (NBS) instrument IN16B8,9 at the ILL, Grenoble, France (Supplemental Figure S1), a setup commonly used with proteins consists of Si 111 crystals for the analyzers with a Doppler drive for tuning the incoming wavelength (Supplemental Figure S2A), thereby giving access to the momentum transfer range ~0.2 &#197;-1 &#60; q &#60; ~2 &#197;-1 and energy transfer range of -30 &#181;eV &#60; <img alt="Equation 3" src="/files/ftp_upload/63664/63664eq03.jpg" style="margin: auto;" /> &#60; 30 &#181;eV-corresponding to timescales ranging from a few ps to a few ns and distances of a few &#197;. In addition, IN16B offers the possibility to perform elastic and inelastic fixed-window scans (E/IFWS)10, which include data acquisition at a fixed energy transfer. As the flux is limited when working with neutrons, E/IFWS allows maximization of the flux for one energy transfer, thus reducing the acquisition time needed to obtain a satisfying signal-to-noise ratio. A more recent option is the backscattering and time-of-flight spectrometer (BATS) mode11, which allows measurement of a wide range of energy transfers, (e.g., -150 &#181;eV &#60; <img alt="Equation 3" src="/files/ftp_upload/63664/63664eq03.jpg" style="margin: auto;" /> &#60; 150 &#181;eV), with a higher flux than with the Doppler drive, yet at the cost of a lower energy resolution (Supplemental Figure S2B).
An important property of neutron scattering is that the incoherent cross section&#160;&#963;inc has a 40 times higher value for hydrogen than for deuterium and is negligible for other elements commonly found in biological samples. Therefore, the dynamics of proteins in a liquid environment can be studied by using a deuterated buffer, and the powder state allows for the study of either protein internal dynamics with hydrogenated protein powder hydrated with D2O, or the study of hydration water for perdeuterated protein powder hydrated with H2O. In the liquid state, neutron backscattering typically allows simultaneously accessing of the center-of-mass self-diffusion of proteins (Fickian-type diffusion) and their internal dynamics. The latter are backbone and side-chain motions usually described by the so-called jump diffusion model or others3,18. In hydrogenated protein powders, the protein diffusion is absent and only internal dynamics needs to be modeled. For hydration water, the contributions of translational and rotational motions of water molecules present a different dependence on the momentum transfer q, which allows for their distinction in the data analysis process17.
This paper illustrates the neutron backscattering method with the study of proteins that were found to be able to unfold, aggregate into a canonical form consisting of stacks of &#946;-strands-the so-called cross-&#946; pattern19,20-and form elongated fibers. This is the so-called amyloid aggregation, which is extensively studied due to its central role in neurodegenerative disorders such as Alzheimer&#39;s or Parkinson&#39;s diseases21,22. The study of the amyloid proteins is also motivated by the functional role they can play23,24 or their high potential for the development of novel biomaterials25. The physicochemical determinants of the amyloid aggregation remain unclear, and no general theory of amyloid aggregation is available, despite tremendous progress during the past years21,26.
Amyloid aggregation implies changes in protein structure and stability with time, the study of which naturally implies dynamics, linked to protein conformation stability, protein function, and protein energy landscape27. Dynamics is directly linked to the stability of a specific state through the entropic contribution for the fastest motions28, and protein function can be sustained by motions on various timescales from sub-ps for light-sensitive proteins29 to ms for domain motions, which can be facilitated by picosecond-nanosecond dynamics30.
Two examples of using neutron backscattering spectroscopy to study amyloid proteins will be presented, one in the liquid state to study protein dynamics and one in the hydrated powder state to study hydration water dynamics. The first example concerns the aggregation of lysozyme into &#181;m sized spheres (called particulates) followed in real time5, and the second a comparison of water dynamics in native and aggregated states of the human protein tau31.
Lysozyme is an enzyme involved in immune defense and is composed of 129 amino acid residues. Lysozyme can form particulates in deuterated buffer at pD of 10.5 and at a temperature of 90 &#176;C. With neutron scattering, we showed that the time evolution of the center-of-mass diffusion coefficient of lysozyme follows the single exponential kinetics of thioflavin T fluorescence (a fluorescent probe used to monitor the formation of amyloid cross-&#946; patterns32), indicating that the formation particulate superstructures and cross-&#946; patterns occur in a single step with the same rate. Moreover, the internal dynamics remained constant throughout the aggregation process, which can be explained either by a fast conformational change that cannot be observed on NBS instruments, or by the absence of significant change in protein internal energy upon aggregation.
The human protein tau is an intrinsically disordered protein (IDP) consisting of 441 amino acids for the so-called 2N4R isoform, which is notably involved in Alzheimer&#39;s disease33. Using neutron backscattering on powders of perdeuterated protein tau, we showed that hydration water dynamics is increased in the fiber state, with a higher population of water molecules undergoing translational motions. The result suggests that an increase in hydration water entropy might drive the amyloid fibrillation of tau.

<table><tbody><tr><td>Aluminum sample holder</td><td></td><td></td><td>Not commercially available. Either the local contact on the instrument can provide them or they can be manufactured based on a technical drawing that can be provided by the local contact.</td></tr><tr><td>Deuterium chloride, 35 wt. % in D&lt;sub&gt;2&lt;/sub&gt;O, &amp;ge;99 atom % D</td><td>Sigma-Aldrich</td><td>&lt;br/&gt; 543047</td><td></td></tr><tr><td>Deuterium oxide (D, 99.9%)</td><td>Eurisotop</td><td>DLM-4DR-PK</td><td></td></tr><tr><td>Dow Corning high-vacuum silicone grease</td><td>Sigma-Aldrich</td><td>Z273554-1EA</td><td></td></tr><tr><td>Ethanol 96%, EMSURE Reag. Ph Eur</td><td>Sigma-Aldrich</td><td>1.5901</td><td></td></tr><tr><td>Glass dessicator</td><td>VWR</td><td>&amp;nbsp; 75871-660</td><td></td></tr><tr><td>Glass dessicator plate, 140 mm</td><td>VWR</td><td>89038-068</td><td></td></tr><tr><td>Indium wire, 1.0 mm (0.04 in) dia, Puratronic, 99.999%</td><td>Alfa Aesar</td><td>00470.G1</td><td></td></tr><tr><td>Lysozyme from chicken egg white dialyzed, lyophilized, powder, ~100,000 U/mg</td><td>Sigma-Aldrich</td><td>62970</td><td></td></tr><tr><td>nPDyn</td><td></td><td>v3.x</td><td>see github.com/kpounot/nPDyn, model functions fot fitting also included in the software</td></tr><tr><td>OHAUS AX324 Adventurer balance, internal calibration</td><td>Dutscher</td><td>92641</td><td></td></tr><tr><td>Phosphorus pentoxide, ReagentPlus, 99%</td><td>Sigma-Aldrich</td><td>214701</td><td></td></tr><tr><td>Pipette ErgoOne 0.5-10 &amp;mu;L</td><td>Starlab</td><td>S7100-0510</td><td></td></tr><tr><td>Pipette ErgoOne 100-1,000 &amp;mu;L</td><td>Starlab</td><td>S7100-1000</td><td></td></tr><tr><td>Pipette ErgoOne 20-200 &amp;mu;L</td><td>Starlab</td><td>S7100-2200</td><td></td></tr><tr><td>Pipette tip TipOne 1,000 &amp;mu;L</td><td>Starlab</td><td>S1111-6001</td><td></td></tr><tr><td>Pipette tip TipOne 10 &amp;mu;L</td><td>Starlab</td><td>S1111-3200</td><td></td></tr><tr><td>Pipette tip TipOne 200 &amp;mu;L</td><td>Starlab</td><td>S1111-0206</td><td></td></tr><tr><td>Sodium deuteroxide solution, 40 wt. % in D&lt;sub&gt;2&lt;/sub&gt;O, 99.5 atom % D</td><td>Sigma-Aldrich</td><td>372072</td><td></td></tr></tbody></table>

high-resolution neutron spectroscopy to study picosecond-nanosecond dynamics of proteins and hydration water

Neutron scattering offers the possibility to probe the dynamics within samples for a wide range of energies in a nondestructive manner and without labeling other than deuterium. In particular, neutron backscattering spectroscopy records the scattering signals at multiple scattering angles simultaneously and is well suited to study the dynamics of biological systems on the ps-ns timescale. By employing D2O-and possibly deuterated buffer components-the method allows monitoring of both center-of-mass diffusion and backbone and side-chain motions (internal dynamics) of proteins in liquid state.
Additionally, hydration water dynamics can be studied by employing powders of perdeuterated proteins hydrated with H2O. This paper presents the workflow employed on the instrument IN16B at the Institut Laue-Langevin (ILL) to investigate protein and hydration water dynamics. The preparation of solution samples and hydrated protein powder samples using vapor exchange is explained. The data analysis procedure for both protein and hydration water dynamics is described for different types of datasets (quasielastic spectra or fixed-window scans) that can be obtained on a neutron backscattering spectrometer.
The method is illustrated with two studies involving amyloid proteins. The aggregation of lysozyme into &#181;m sized spherical aggregates-denoted particulates-is shown to occur in a one-step process on the space and time range probed on IN16B, while the internal dynamics remains unchanged. Further, the dynamics of hydration water of tau was studied on hydrated powders of perdeuterated protein. It is shown that translational motions of water are activated upon the formation of amyloid fibers. Finally, critical steps in the protocol are discussed as to how neutron scattering is positioned regarding the study of dynamics with respect to other experimental biophysical methods.

The aggregation of lysozyme into particulates was performed at 90 &#176;C with a protein concentration of 50 mg/mL in a deuterated buffer (0.1 M NaCl at pD 10.5). The formation of particulates is triggered by the temperature increase to 90 &#176;C and occurs within 6 h (Supplemental Figure S8). The data acquisition was performed on IN16B, as described in the protocol above (data are permanently curated by the ILL and accessible at&#160;http://dx.doi.org/10.5291/ILL-DATA.8-04-811).
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Watch this Scientific Journal Video about High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water at JoVE.com

High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water

Neutron backscattering spectroscopy offers a nondestructive and label-free access to the ps-ns dynamics of proteins and their hydration water. The workflow is presented with two studies on amyloid proteins: on the time-resolved dynamics of lysozyme during aggregation and on the hydration water dynamics of tau upon fiber formation.

Neutron scattering offers the possibility to probe the dynamics within samples for a wide range of energies in a nondestructive manner and without ...

high-resolution-neutron-spectroscopy-to-study-picosecond-nanosecond

Research

JoVE Journal

Biochemistry

1.7K Views.  Universität Tübingen. Neutronenbackscatterings meten de globale diffusie en interne dynamiek van eiwitten en hydratatiewater zonder stralingsschade. Neutronenspectroscopie heeft tegelijkertijd toegang tot ruimtelijke en tijdscorrelaties op moleculair niveau. In zachte materie en biologische materialen is het bijzonder interessant om indirecte informatie te verkrijgen over de lokale orde op deze langeafstandsstoornissystemen.Dus neutronenverstrooiing kan worden gebruikt om dynamica in biologie, scheikunde of...

Video: High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water

Nuclear Magnetic Resonance Spectroscopy for the Identification of Multiple Phosphorylations of Intrinsically Disordered Proteins

Aggregates of the neuronal Tau protein are found inside neurons of Alzheimer's disease patients. Development of the disease is accompanied by increased, abnormal phosphorylation of Tau. In the course of the molecular investigation of Tau functions and dysfunctions in the disease, nuclear magnetic resonance (NMR) spectroscopy is used to identify the multiple phosphorylations of Tau. We present here detailed protocols of recombinant production of Tau in bacteria, with isotopic enrichment for NMR studies. Purification steps that take advantage of Tau's heat stability and high isoelectric point are described. The protocol for in vitro phosphorylation of Tau by recombinant activated ERK2 allows for generating multiple phosphorylations. The protein sample is ready for data acquisition at the issue of these steps. The parameter setup to start recording on the spectrometer is considered next. Finally, the strategy to identify phosphorylation sites of modified Tau, based on NMR data, is explained. The benefit of this methodology compared to other techniques used to identify phosphorylation sites, such as immuno-detection or mass spectrometry (MS), is discussed.

We describe here a method to identify multiple phosphorylations of an intrinsically disordered protein by Nuclear Magnetic Resonance Spectroscopy (NMR), using Tau protein as a case study. Recombinant Tau is isotopically enriched and modified in vitro by a kinase prior to data acquisition and analysis.

Aggregates of the neuronal Tau protein are found inside neurons of Alzheimer's disease patients. Development of the disease is accompanied by increased, ...

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. ...

Isolation of Intermediate Filament Proteins from Multiple Mouse Tissues to Study Aging-associated Post-translational Modifications

Intermediate filaments (IFs), together with actin filaments and microtubules, form the cytoskeleton &#8211; a critical structural element of every cell. Normal functioning IFs provide cells with mechanical and stress resilience, while a dysfunctional IF cytoskeleton compromises cellular health and has been associated with many human diseases. Post-translational modifications (PTMs) critically regulate IF dynamics in response to physiological changes and under stress conditions. Therefore, the ability to monitor changes in the PTM signature of IFs can contribute to a better functional understanding, and ultimately conditioning, of the IF system as a stress responder during cellular injury. However, the large number of IF proteins, which are encoded by over 70 individual genes and expressed in a tissue-dependent manner, is a major challenge in sorting out the relative importance of different PTMs. To that end, methods that enable monitoring of PTMs on IF proteins on an organism-wide level, rather than for isolated members of the family, can accelerate research progress in this area. Here, we present biochemical methods for the isolation of the total, detergent-soluble, and detergent-resistant fraction of IF proteins from 9 different mouse tissues (brain, heart, lung, liver, small intestine, large intestine, pancreas, kidney, and spleen). We further demonstrate an optimized protocol for rapid isolation of IF proteins by using lysing matrix and automated homogenization of different mouse tissues. The automated protocol is useful for profiling IFs in experiments with high sample volume (such as in disease models involving multiple animals and experimental groups). The resulting samples can be utilized for various downstream analyses, including mass spectrometry-based PTM profiling. Utilizing these methods, we provide new data to show that IF proteins in different mouse tissues (brain and liver) undergo parallel changes with respect to their expression levels and PTMs during aging.

In this method, we present biochemical procedures for rapid and efficient isolation of intermediate filament (IF) proteins from multiple mouse tissues. Isolated IFs can be used to study changes in post-translational modifications by mass spectrometry and other biochemical assays.

Intermediate filaments (IFs), together with actin filaments and microtubules, form the cytoskeleton &#8211; a critical structural element of every cell. ...

Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

Monitoring the dynamics of protonation and protein backbone conformation changes during the function of a protein is an essential step towards understanding its mechanism. Protonation and conformational changes affect the vibration pattern of amino acid side chains and of the peptide bond, respectively, both of which can be probed by infrared (IR) difference spectroscopy. For proteins whose function can be repetitively and reproducibly triggered by light, it is possible to obtain infrared difference spectra with (sub)microsecond resolution over a broad spectral range using the step-scan Fourier transform infrared technique. With ~102-103 repetitions of the photoreaction, the minimum number to complete a scan at reasonable spectral resolution and bandwidth, the noise level in the absorption difference spectra can be as low as ~10-4, sufficient to follow the kinetics of protonation changes from a single amino acid. Lower noise levels can be accomplished by more data averaging and/or mathematical processing. The amount of protein required for optimal results is between 5-100 &#181;g, depending on the sampling technique used. Regarding additional requirements, the protein needs to be first concentrated in a low ionic strength buffer and then dried to form a film. The protein film is hydrated prior to the experiment, either with little droplets of water or under controlled atmospheric humidity. The attained hydration level (g of water / g of protein) is gauged from an IR absorption spectrum. To showcase the technique, we studied the photocycle of the light-driven proton-pump bacteriorhodopsin in its native purple membrane environment, and of the light-gated ion channel channelrhodopsin-2 solubilized in detergent.

Key steps of protein function, in particular backbone conformational changes and proton transfer reactions, often take place in the microsecond to millisecond time scale. These dynamical processes can be studied by time-resolved step-scan Fourier-transform infrared spectroscopy, in particular for proteins whose function is triggered by light.

Monitoring the dynamics of protonation and protein backbone conformation changes during the function of a protein is an essential step towards ...

Engineering

Study of Protein Dynamics via Neutron Spin Echo Spectroscopy

Most human body proteins' activity and functionality are related to configurational changes of entire subdomains within the protein crystal structure. The crystal structures build the basis for any calculation that describes the structure or dynamics of a protein, most of the time with strong geometrical restrictions. However, these restrictions from the crystal structure are not present in the solution. The structure of the proteins in the solution may differ from the crystal due to rearrangements of loops or subdomains on the pico to nanosecond time scale (i.e., the internal protein dynamics time regime). The present work describes how slow motions on timescales of several tens of nanoseconds can be accessed using neutron scattering. In particular, the dynamical characterization of two major human proteins, an intrinsically disordered protein that lacks a well-defined secondary structure and a classical antibody protein, is addressed by neutron spin echo spectroscopy (NSE) combined with a wide range of laboratory characterization methods. Further insights into protein domain dynamics were achieved using mathematical modeling to describe the experimental neutron data and determine the crossover between combined diffusive and internal protein motions. The extraction of the internal dynamic contribution to the intermediate scattering function obtained from NSE, including the timescale of the various movements, allows further vision into the mechanical properties of single proteins and the softness of proteins in their nearly natural environment in the crowded protein solution.

Study of Protein Dynamics via Neutron Spin Echo Spectroscopy

The present protocol describes methods for investigating the structure and dynamics of two model proteins that have an important role in human health. The technique combines bench-top biophysical characterization with neutron spin echo spectroscopy to access the dynamics at time and length scales relevant for protein interdomain motions.

Most human body proteins' activity and functionality are related to configurational changes of entire subdomains within the protein crystal structure. The ...

Studying Soft-matter and Biological Systems over a Wide Length-scale from Nanometer and Micrometer Sizes at the Small-angle Neutron Diffractometer KWS-2

The KWS-2 SANS diffractometer is dedicated to the investigation of soft matter and biophysical systems covering a wide length scale, from nm to &#181;m. The instrument is optimized for the exploration of the wide momentum transfer Q range between 1x10-4 and 0.5 &#197;-1 by combining classical pinhole, focusing (with lenses), and time-of-flight (with chopper) methods, while simultaneously providing high-neutron intensities with an adjustable resolution. Because of its ability to adjust the intensity and the resolution within wide limits during the experiment, combined with the possibility to equip specific sample environments and ancillary devices, the KWS-2 shows a high versatility in addressing the broad range of structural and morphological studies in the field. Equilibrium structures can be studied in static measurements, while dynamic and kinetic processes can be investigated over time scales between minutes to tens of milliseconds with time-resolved approaches. Typical systems that are investigated with the KWS-2 cover the range from complex, hierarchical systems that exhibit multiple structural levels (e.g., gels, networks, or macro-aggregates) to small and poorly-scattering systems (e.g., single polymers or proteins in solution). The recent upgrade of the detection system, which enables the detection of count rates in the MHz range, opens new opportunities to study even very small biological morphologies in buffer solution with weak scattering signals close to the buffer scattering level at high Q.
In this paper, we provide a protocol to investigate samples with characteristic size levels spanning a wide length scale and exhibiting ordering in the mesoscale structure using KWS-2. We present in detail how to use the multiple working modes that are offered by the instrument and the level of performance that is achieved.

Here, we present a protocol to investigate soft matter and biophysical systems over a wide mesoscopic length scale, from nm to &#181;m that involves the use of the KWS-2 SANS diffractometer at high intensities and an adjustable resolution.

The KWS-2 SANS diffractometer is dedicated to the investigation of soft matter and biophysical systems covering a wide length scale, from nm to &#181;m. ...

Bioengineering

Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures

Neutron crystallography is a structural technique that allows determination of hydrogen atom positions within biological macromolecules, yielding mechanistically important information about protonation and hydration states while not inducing radiation damage. X-ray diffraction, in contrast, provides only limited information on the position of light atoms and the X-ray beam&#160;rapidly induces radiation damage of photosensitive&#160;cofactors and metal centers. Presented here is the workflow employed for the IMAGINE and MaNDi beamlines at Oak Ridge National Laboratory (ORNL) to obtain a neutron diffraction structure once a protein crystal of suitable size (&#62; 0.1 mm3) has been grown. We demonstrate mounting of hydrogenated protein&#160;crystals in quartz capillaries for neutron diffraction data collection. Also presented is the vapor exchange process of the mounted crystals with D2O-containing buffer to ensure replacement of hydrogen atoms at exchangeable sites with deuterium. The incorporation of deuterium reduces the background arising from the incoherent scattering of hydrogen atoms and prevents density cancellation caused by their negative coherent scattering length. Sample alignment and room temperature data collection strategies are illustrated using quasi-Laue data collection at IMAGINE at the High Flux Isotope Reactor (HFIR). Furthermore, crystal mounting and rapid freezing in liquid nitrogen for cryo-data collection to trap labile reaction intermediates is demonstrated at the MaNDi time-of-flight instrument at the Spallation Neutron Source (SNS). Preparation of the model coordinate and diffraction data files and visualization of the neutron scattering length density (SLD) maps will also be addressed. Structure refinement against neutron data-only or against joint X-ray/neutron data to obtain an all-atom structure of the protein of interest will finally be discussed. The process of determining a neutron structure will be demonstrated using crystals of the lytic polysaccharide monooxygenase Neurospora crassa LPMO9D, a copper-containing metalloprotein involved in the degradation of recalcitrant polysaccharides via oxidative cleavage of the glycosidic bond.

Neutron protein crystallography is a structural technique that permits the localization of hydrogen atoms, thereby providing important mechanistic details of protein function. We present here the workflow for mounting a protein crystal, neutron diffraction data collection, structure refinement and analysis of the neutron scattering length density maps.

Neutron crystallography is a structural technique that allows determination of hydrogen atom positions within biological macromolecules, yielding ...

Chemistry

Protocol for NMR 15N Relaxation and hetNOE Experiments in Protein Dynamics Study

NMR 15N Relaxation Experiments for the Investigation of Picosecond to Nanoseconds Structural Dynamics of Proteins

Nuclear magnetic resonance (NMR) spectroscopy allows studying proteins in solution and under physiological temperatures. Frequently, either the amide groups of the protein backbone or the methyl groups in side chains are used as reporters of structural dynamics in proteins. A structural dynamics study of the protein backbone of globular proteins on 15N labeled and fully protonated samples usually works well for proteins with a molecular weight of up to 50 kDa. When side chain deuteration in combination with transverse relaxation optimized spectroscopy (TROSY) is applied, this limit can be extended up to 200 kDa for globular proteins and up to 1 MDa when the focus is on the side chains. When intrinsically disordered proteins (IDPs) or proteins with intrinsically disordered regions (IDRs) are investigated, these weight limitations do not apply but can go well beyond. The reason is that IDPs or IDRs, characterized by high internal flexibility, are frequently dynamically decoupled. Various NMR methods offer atomic-resolution insights into structural protein dynamics across a wide range of time scales, from picoseconds up to hours. Standard 15N relaxation measurements overview a protein&#39;s internal flexibility and characterize the protein backbone dynamics experienced on the fast pico- to nanosecond timescale. This article presents a hands-on protocol for setting up and recording NMR 15N R1, R2, and heteronuclear Overhauser effect (hetNOE) experiments. We show exemplary data and explain how to interpret them simply qualitatively before any more sophisticated analysis.

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments

Nuclear magnetic resonance (NMR) spectroscopy can characterize structural protein dynamics in a residue-specific manner. We provide a hands-on protocol for recording NMR 15N R1 and R2 relaxation and {1H}-15N heteronuclear Overhauser effect (hetNOE) experiments, sensitive to the picoseconds to nanoseconds timescale.

Nuclear magnetic resonance (NMR) spectroscopy allows studying proteins in solution and under physiological temperatures. Frequently, either the amide ...

Millisecond Hydrogen/Deuterium-Exchange Mass Spectrometry for the Study of Alpha-Synuclein Structural Dynamics Under Physiological Conditions

Alpha-synuclein (aSyn) is an intrinsically disordered protein whose fibrillar aggregates are abundant in Lewy bodies and neurites, which are the hallmarks of Parkinson's disease. Yet, much of its biological activity, as well as its aggregation, centrally involves the soluble monomer form of the protein. Elucidation of the molecular mechanisms of aSyn biology and pathophysiology requires structurally highly resolved methods and is sensitive to biological conditions. Its natively unfolded, meta-stable structures make monomeric aSyn intractable to many structural biology techniques. Here, the application of one such approach is described: hydrogen/deuterium-exchange mass spectrometry (HDX-MS) on the millisecond timescale for the study of proteins with low thermodynamic stability and weak protection factors, such as aSyn. At the millisecond timescale, HDX-MS data contain information on the solvent accessibility and hydrogen-bonded structure of aSyn, which are lost at longer labeling times, ultimately yielding structural resolution up to the amino acid level. Therefore, HDX-MS can provide information at high structural and temporal resolutions on conformational dynamics and thermodynamics, intra- and inter-molecular interactions, and the structural impact of mutations or alterations to environmental conditions. While broadly applicable, it is demonstrated how to acquire, analyze, and interpret millisecond HDX-MS measurements in monomeric aSyn.

The structural ensemble of monomeric alpha-synuclein affects its physiological function and physicochemical properties. The present protocol describes how to perform millisecond hydrogen/deuterium-exchange mass spectrometry and subsequent data analyses to determine conformational information on the monomer of this intrinsically disordered protein under physiological conditions.

Alpha-synuclein (aSyn) is an intrinsically disordered protein whose fibrillar aggregates are abundant in Lewy bodies and neurites, which are the hallmarks ...

Neuroscience

Neutron Spin Echo Spectroscopy as a Unique Probe for Lipid Membrane Dynamics and Membrane-Protein Interactions

Lipid bilayers form the main matrix of cell membranes and are the primary platform for nutrient exchange, protein-membrane&#160;interactions, and viral budding, among other vital cellular processes. For efficient biological activity, cell membranes should be rigid enough to maintain the integrity of the cell and its compartments yet fluid enough to allow membrane components, such as proteins and functional domains, to diffuse and interact. This delicate balance of elastic and fluid membrane properties, and their impact on biological function, necessitate a better understanding of collective membrane dynamics over mesoscopic length and time scales of key biological processes, e.g., membrane deformations and protein binding events. Among the techniques that can effectively probe this dynamic range is neutron spin echo (NSE) spectroscopy. Combined with deuterium labeling, NSE can be used to directly access bending and thickness fluctuations as well as mesoscopic dynamics of select membrane features. This paper provides a brief description of the NSE technique and outlines the procedures for performing NSE experiments on liposomal membranes, including details of sample preparation and deuteration schemes, along with instructions for data collection and reduction. The paper also introduces data analysis methods used to extract key membrane parameters, such as the bending rigidity modulus, area compressibility modulus, and in-plane viscosity. To illustrate the biological importance of NSE studies, select examples of membrane phenomena probed by NSE are discussed, namely, the effect of additives on membrane bending rigidity, the impact of domain formation on membrane fluctuations, and the dynamic signature of membrane-protein interactions.

This paper describes the protocols for sample preparation, data reduction, and data analysis in neutron spin echo (NSE) studies of lipid membranes. Judicious deuterium labeling of lipids enables access to different membrane dynamics on mesoscopic length and time scales, over which vital biological processes occur.

Lipid bilayers form the main matrix of cell membranes and are the primary platform for nutrient exchange, protein-membrane&#160;interactions, and viral ...

High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water

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