We would like to thank Karl-Peter Hopfner and Robert Thomas Byrne for kindly providing HerA and HerA-NurA protein samples and for their help with experimental design. We also thank Dr. Eamonn Reading for his review of the manuscript. We gratefully acknowledge our funding bodies: Wellcome Trust [109854/Z/15/Z] and Royal Society [RG150216 to A.P.].

1. Sample Preparation for Native MS of Protein and Protein-Ligand Complexes
NOTE: To gain an understanding of the molecular basis of a protein complex and ligand binding using native MS, suitable sample preparation is key. The aim of this section is to highlight the essential sample preparation steps prior to MS analysis using the HerA-NurA complex which binds DNA and nucleotides as an example.
<ol>
	<li>Prepare 20 &#181;L aliquots of concentrated purified protein (typically 15 - 30 &#181;M) in a 1.5 mL tube.</li>
	<li>For ATP or ADP binding analysis 
	NOTE: Add increasing concentrations of the non-hydrolyzable ATP analog adenosine 5&#8242;-O-(3-thiotriphosphate), tetralithium salt (ATP-&#947;-S) or adenosine 5&#8242;-diphosphate (ADP). Non-hydrolyzable ATP derivatives generate a stable complex which would enable the ATP-bound protein to be captured. Other non-hydrolysable ATP analogues that could be tested include AMP-PNP and ATP-&#947;-S-Mg2+.
	<ol>
		<li>For HerA-NurA studies, mix 5 &#181;M of purified protein with ATP-&#947;-S and ADP at concentrations ranging from 0-1 mM.</li>
		<li>To capture simultaneous ATP-&#947;-S and ADP binding, add both nucleotides at the same or varying concentrations.</li>
		<li>Add 2 mM MgCl2 and incubate at 25 &#176;C in a dry bath incubator for 1 h. 
		NOTE: Analysis of nucleotide binding using nESI native MS can result in artefactual binding at high concentrations, therefore non-specific binding must be taken into account29. To investigate non-specific binding, add a higher concentration of nucleotides between 2-5 mM).</li>
	</ol>
	</li>
	<li>For DNA binding analysis
	<ol>
		<li>Mix the protein and DNA at a molar ratio that allows for protein-DNA complex formation. For HerA and HerA-NurA, mix 5 &#181;M of purified protein with DNA at a 1:1 ratio.</li>
		<li>Incubate the HerA-NurA or HerA - DNA mixture for 30 min at 25 &#176;C in a dry bath incubator until it reaches equilibrium. The duration and temperature of incubation may vary depending on the protein under investigation.</li>
		<li>Buffer exchange protein samples to MS compatible buffers. Commonly, aqueous ammonium acetate solution between 5 mM-1 M at pH 7-8 are used. Other MS compatible buffers include ethylenediammonium diacetate (EDDA) and Triethylammonium acetate (TEAA)30. For HerA-NurA studies, use 200 mM ammonium acetate pH 7. 
		NOTE: There are several methods for buffer exchange prior to analysis by MS such as using a spin concentrator or chromatography columns. Native MS is mostly limited by the quality of the sample such as buffers and adducts used during purification. Therefore, it is essential to perform sufficient desalting to obtain resolved peaks.</li>
		<li>For HerA-NurA ligand binding studies, buffer exchange samples 6-8 times into 200 mM ammonium acetate using a concentrator.Although this method is more time consuming, it ensures that resolved peaks are achieved and allows for accurate mass determination of ATP/ADP bound species.</li>
	</ol>
	</li>
</ol>
2. Native MS Acquisition and Analysis for Investigating Protein Complexes and Protein-Ligand Complexes
Note: MS conditions should be optimized to achieve highly resolved peaks to enable accurate mass measurements. This section details optimized parameters on a Q-ToF mass spectrometer with a 32k upper limit m/z quadrupole.
<ol>
	<li>Prepare in-house capillaries for nano-electrospray and perform instrument mass calibration for accurate mass measurements as detailed by Kirshenbaum et al.1.</li>
	<li>Select sensitivity, positive ion acquisition and mobility TOF modes.</li>
	<li>Turn on the Trap, API and IMS gases. For IM separation, use nitrogen (60 mL/min) and argon (8.4 mL/min for the trap region) as starting points and then adjust.</li>
	<li>Set an appropriate m/z acquisition range. For an unknown protein, initial optimization steps should use a wide range such as 500-32,000 m/z.</li>
	<li>Load 2-3 &#181;L of the protein complex solution to be analyzed into a gold coated capillary and insert it into a capillary holder.</li>
	<li>Gently tighten the capillary and place the capillary in the electrospray source stage and slide the stage into position to start acquiring data.</li>
	<li>Apply low nano-flow gas pressure (0.00-0.05 Bar) until a drop is formed at the tip of the capillary. The nano-flow pressure can then be dropped until the spray is maintained.</li>
	<li>Adjust the capillary with respect to the cone by moving the capillary in x, y, z positions and monitor the ion current to achieve a stable ion current. Apply a capillary voltage in the range of 0.9-1.6 kV.</li>
	<li>Set the sampling cone (50-120 V), source offset (60.0), source temperature (25 &#176;C) and cone gas flow (0.0 L/h). These suggested initial conditions can be adjusted.</li>
	<li>To acquire a well resolved mass spectrum and to maximize ion transmission, adjust MS parameters and monitor the resulting change in the spectra. These include adjusting the gas flow in the Trap (2-8 mL/min), He Cell (180 mL/min) and IMS cell (90 mL/min) to achieve best separation at maximum transmission.</li>
	<li>Adjust the trap collision energies if voltage offsets are insufficient. An optimal starting point is between 10-50 V. 
	NOTE: Increasing the trap energy can remove non-covalently bound adducts. However, take care to avoid collision induced dissociation and unfolding of the protein-ligand complex. Perform ion mobility measurements to check if instrument conditions retain the protein in the native folded state (Step 3).</li>
	<li>Improve desolvation by optimizing the trap bias voltage. An optimal starting point is 20-45 V.</li>
	<li>Optimize the wave velocity and wave height to achieve best mobility separation. A detailed explanation and protocol can be found here31. For the HerA-NurA studies, use wave velocity of 40 (m/s) and wave height of 550-650 (V).</li>
	<li>Use all other parameters as instrument default values.</li>
	<li>Prepare a ligand-free sample for analysis as a control for each run (Figure 1). For ligand binding experiments, perform at least three independent measurements.</li>
	<li>Use the Masslynx software to measure masses of generated species and identify the ligand binding, such as ATP and ADP binding and oligomeric states (Figure 2 and 3).Other software available include UniDec32, PULSAR33 and Amphitrite34.</li>
	<li>To quantify the relative abundance of species, use the corresponding ion intensities observed in the raw ESI-MS spectra (for example ligand bound, different oligomers, etc.). Alternatively, perform quantification using specialized software like UniDec and Massign35 (Figure 1 and 3 ).</li>
</ol>
3. Acquiring and Analyzing IM-MS
NOTE: IM-MS separates ions in the gas-phase based on their size (mass), shape and charge. Every feature resolved in m/z spectrum is associated with a drift time distribution. IM-MS measures the drift-time of an ion which can be used to calculate the collision cross section (CCS). Drift time values measured from IM-MS data acquired using a drift-tube can be linearly correlated to CCS values36. For travelling wave IM-MS (TWIMS) measurements, calculating CCS values requires a calibration curve obtained from protein standards with known CCS values37.Compact structures travel faster than extended or elongated structures due to reduced interactions with buffer gas in the mobility cell38. Therefore, IM-MS can be used to detect if the native folded structure has been retained in the gas phase39,40. This section outlines how to measure IM-MS and calculate the CCS of protein using TWIMS.
<ol>
	<li>After optimizing instrument conditions for stable transmission (Step 2), reduce the collisional energy and sampling cone as low as possible whilst retaining good spectra quality.</li>
	<li>Use the optimized wave velocity and wave height to acquire IM-MS (Step 2).</li>
	<li>Measure the ion drift time with IM-MS at three different wave velocities (e.g., 550, 600 and 650 m/s) whilst maintaining the same wave height (e.g., 40 V).</li>
	<li>To determine the protein ions CCS, measure protein calibrants under the same instrument conditions used for protein under investigation. Optimal drift-time calibration requires measurement of proteins with known CCS.
	<ol>
		<li>Select four calibrants, two with a mass above and two with a mass below that of the protein under investigation37. Most importantly, make sure that the wave height and wave velocity are the same as those recorded for the protein under investigation.</li>
	</ol>
	</li>
	<li>Calculate CCS manually41 or using a specialized software such as PULSAR33 and Amphitrite34 (Figure 5).</li>
	<li>To check whether the protein is native-like in the gas-phase, compare experimental CCS to theoretical CCS obtained from high resolution structures. For HerA-NurA, calculate theoretical CCS using the Projection Approximation (PA) method used in MOBCAL42. Other methods include trajectory method (TM)42 and exact hard sphere scattering (EHS)43.</li>
</ol>
4. In-Solution Disruption of Protein Complexes for Native MS and IM-MS Led Structure Determination
Note: Protein sub-complexes can in some cases be identified from the same solution as the intact complex. However, further structural information such as inter-subunit connectivity and complex assembly can be attained from disrupting protein interactions in solution, to form sub-complexes. This can be achieved in several ways such as the addition of organic solvent, increasing the ionic strength or manipulating the pH. To gain insight into the HerA-NurA complex subunit connectivity and complex assembly, sub-complexes were generated in solution by adding solvents which perturb subunit interactions.
<ol>
	<li>Prepare the protein sample and buffer exchange into ammonium acetate as described in Step 1.</li>
	<li>Add 10-40% of solvent in 10% increments. Solvents typically used are Methanol (MeOH), dimethyl sulfoxide (DMSO) or acetonitrile (ACN). 
	NOTE: This can be performed within a polypropylene microcentrifuge tube.</li>
	<li>Incubate the mixture on ice for 1 h.</li>
	<li>Acquire an IM-MS spectrum for each condition (Steps 2 and 3) (Figure 4).</li>
	<li>Use the SUMMIT software44 to assign protein sub-complexes and generate protein interaction networks. Alternatively, manually generate a list of theoretical masses of the expected species.</li>
	<li>To ensure subcomplexes are folded, calculate the experimental CCS values for the sub-complexes and compare to theoretical CCS as explained in Step 3 (Table 1, Figure 5 and Figure 6).</li>
</ol>
5. Investigating Protein Complex Stability using Collision Induced Unfolding (CIU)
Note: CIU can be used probe the structural stability of proteins and their complexes upon ligand binding. Specialist software packages such as PULSAR33, Amphitrite34 and CIU suite9 can then be used to model the gas-phase unfolding of the protein under investigation with and without ligand. As an example, this section outlines procedure for monitoring gas-phase unfolding trajectories and investigating the stabilizing effect of DNA and ATP binding on the HerA-NurA complex.
<ol>
	<li>Record IM-MS data whilst increasing the trap acceleration voltage from 10 V to 200 V in 2-10 V increments to progressively unfold the protein in the gas-phase. 
	NOTE: Recording smaller increments results in more data files to process, however this approach provides more resolved unfolding plot, which is important for analyzing the transition points between folded/unfolded species.</li>
	<li>Analyze the data acquired using PULSAR33, Amphitrite34 or CIU suite9 and generate two-dimensional unfolding plots in units of CCS as a function of accelerating voltage (Step 3). For each charge state, this is created by stacking the intensity- normalized CCS distributions at each accelerating voltage (Figure 7 A-Bi).</li>
	<li>Generate a theoretical unfolding plot using one of the software packages. The data will be fitted to an unfolding model. This makes it possible to quantify the collisional energy at which unfolding transitions occur and determine the stability of proteins with and without bound ligands33. An unfolding transition is when a species transitions from one state (based on their experimental CCS values) to another state with a larger CCS.</li>
	<li>To quantitate the transitions, calculate the transitional midpoint(s) between states using algorithms and software such as PULSAR33. This is commonly reported as CV50, which is the collision (trap) voltage value at which 50% of a specific state is depleted.</li>
	<li>Using the CV50 value, calculate the total internal energy of an ion using the center-of-mass collision energy (KECOM)45. KECOM is defined by the total internal energy available for the unfolding transition of an ion and is calculated from the kinetic energy and masses of the collision partners (protein ion and neutral gas) as described in equation (1)10 
	KEcom (eV) = <img alt="Equation 1" src="/files/ftp_upload/57966/57966eq1.jpg" /> (equation 1). 
	Where Z is the ion charge, MN is the mass of the neutral gas and MION is the mass of the protein ion. 
	NOTE: This is because CIU of proteins is charge dependent46,47. It is recommended to perform the KECOM analysis to more than one charge state ( Figure 7Aii).</li>
</ol>
6. Modelling Procedures for Differential Molecular Dynamics Simulations used in Integrative MS
NOTE: Using models of protein subunits or complexes such as from crystal structures, differential MD simulations (protein complex with and without ligand) can be used to determine effects of for example ligand presence on protein structure and dynamics. This section details a workflow and tools needed for modelling procedures necessary to set-up differential molecular dynamics simulations.
<ol>
	<li>Identify the subunits which compose the complex (Figure 8A, in Steps 2 and 3). Source existing models of subunits, e.g., crystal structures from the RCSB databank (https://www.rcsb.org). The UniProt entry of the protein will contain a list of know crystallographic/NMR structures (http://www.uniprot.org). If these are not available, the theoretical sequence can be input to BLAST to identify suitable templates for homology modelling (http://blast.ncbi.nlm.nih.gov/).</li>
	<li>Assemble the complex in the correct topology (Figure 8A-ii). This can be done through various methods. The individual subunits can be fitted into available electron microscopy maps found on the EMDB to assemble the intact complex (https://www.ebi.ac.uk/pdbe/emdb/). A tutorial for fitting PDBs into EM maps using Molecular Dynamics Flexible Fitting (MDFF) can be found here: http://www.ks.uiuc.edu/Training/Tutorials/science/mdff/tutorial_mdff-html/.</li>
	<li>Identify missing regions of the complex (Figure 8A-iii). Perform multiple sequence alignment (MSA) between the PDB and theoretical sequence to identify residues which may be unfitted into crystal structures, or any mutations inherited from crystallographic experiments. MSA can be performed using the webservers such as T-Coffee (http://tcoffee.crg.cat/apps/tcoffee/do:regular).</li>
	<li>Regenerate missing residues via homology modelling (Figure 8A-iv). Missing residues of the protein complex can be built using the MODELLER program (https://salilab.org/modeller/). MODELLER can output an ensemble of n models in different regenerated configurations. Good models can be identified based on their Discrete Optimised Protein Energy (DOPE) score. A comprehensive tutorial is provided on the software website (https://salilab.org/modeller/tutorial/).</li>
	<li>Perform differential molecular dynamics (MD) simulations of the protein complex (Figure 8B) to identify regions of proteins which respond to a particular environmental change, e.g., presence of a ligand. In such simulations, behavioural parameters from Simulation A (protein only) which acts as a reference, is subtracted from Simulation B (protein+ligand). The differential root mean square fluctuation (RMSF) calculated between Simulations A and B can inform on regions of the protein which increase or decrease in flexibility in a ligand dependent manner.
	<ol>
		<li>Perform MD simulations and downstream analysis using GROMACS (http://www.gromacs.org). A tutorial can be found at: http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin/gmx-tutorials/Lysozyme/index.html. To elimate model bias, the structure of the ligand-bound complex should be generated first. The protein is then copied from this without the ligand, to yield a protein model identical to the ligand-bound complex.&#160;</li>
	</ol>
	</li>
</ol>

No conflicts of interest declared.

MS is playing an increasingly important role in characterizing the stoichiometry, interactions and subunit architecture of protein complexes. IM-MS data can be used to define topological arrangements of subunits within multicomponent complexes. Compared to other existing structural biology methods, MS has several advantages. Native MS is a rapid and highly sensitive technique and can be used to probe heterogeneous protein samples. When coupled with in-solution disruption experiments, dissociation pathways of protein assemblies can be monitored. Together with crystal structures or homology models, the information offered by structural MS offers a tool for investigating protein-ligand interactions and provide near-native models and assembly pathways11.
Here, we describe the necessary experimental procedures for analyzing the stoichiometry and composition of protein-ligand interactions, with one or more ligands, using integrative MS. This includes MS sample preparation, data acquisition, data analysis, and the integration of MS data using computational tools. To do this, we used the DNA-resection HerA-NurA hetero-oligomeric protein complex, bound to three ligands (DNA, ATP, and ADP), as our model system. The protocol shows the use of the currently available software to aid data analysis and presentation.
Acquiring high quality spectra is important for ligand binding analysis, therefore, careful sample preparation steps are critical, including protein purification, ligand titration, and buffer exchange. One limitation of nESI native MS when studying ligand binding is non-specific binding. Non-specific binding occurs during droplet desolvation throughout the electrospray process. This increases the ligand concentrations and therefore alters the protein/Ligand ratio29. The binding of nucleotides results in a relatively small mass difference between apo and nucleotide-bound protein which does not alter the ionization efficiency50,51.
We used the Synapt G2-Si MS system for our work, but the protocols are applicable for different investigations of other protein-ligand complexes using other commercially available nano-electrospray mass spectrometers. Integrative structural MS is increasingly playing an important role in addressing biological problems of greater complexity. The workflow and techniques described here are well-suited for understanding the structural consequences and building mechanisms of protein complex and protein-ligand formation which are otherwise difficult to study using conventional structural techniques.

Native mass spectrometric analysis of intact proteins and their complexes is carried out using electrospray and nano-electrospray ionization (nESI), which preserve protein folding and non-covalent interactions during the ionization process1,2. In native MS, the structure of proteins and their complexes are retained in a near-native state in the gas-phase3,4. Native MS detects multiple charged protein ions, which are separated according to their mass to charge ratio (m/z) allowing the mass of the protein or protein-ligand complex to be calculated. This information enables the determination of an intact protein&#39;s stoichiometry, subunit composition, ligand binding, and interaction networks3,4,5,6. Native MS has several advantages compared to other techniques such X-ray crystallography and nuclear magnetic resonance spectroscopy5. Firstly, native MS is a rapid and highly sensitive technique, requiring only a few microliters (2-3 &#181;L) of sample at relatively low final complex concentrations in the high nM to low &#181;M range6. Secondly, native MS can be used to interrogate heterogeneous protein samples making it possible to analyze multiple proteins and oligomeric states simultaneously. Thirdly, native MS does not require protein samples to be modified before analysis by chemical crosslinking or protein labelling. These advantages have made structural MS a powerful tool for the structural investigation of protein complexes.
Native MS can be combined with ion mobility (IM), a technique that measures the time a protein ion takes to travel through an electric field, enabling the collisional cross section (CCS) to be determined. The CCS provides low-resolution structural information, which enables topology and conformational heterogeneity information of proteins to be obtained. Furthermore, it allows the examination of protein structural models generated by computational approaches.
Protein gas-phase stability can be investigated using collision induced unfolding (CIU) measured by IM-MS. During the CIU process, protein ions are accelerated and activated through increased accelerating collisions with an inert buffer gas within a mass spectrometer7,8,9. This collisional activation process causes the protein to partially unfold, which translates into an increase in CCS. This change in CCS and the energy required to unfold the protein can be measured by IM-MS. Using this approach, the effect of ligand binding on protein stability can be measured10. Subcomplexes can be generated in solution using in-solution disruption methods such as the addition of organic solvents to monitor native-like topologies of protein complexes. Disruption of the protein complexes is mainly due to the disruption of intra non-covalent interactions. The sub-complexes maintain native-like topologies and, upon MS detection, reveal information about inter-subunit connectivity.
Integrative approaches in structural biology combine diverse methods to study the structure and dynamics of proteins and their complexes3,4,5,6. Native MS and IM-MS have been used to uncover the molecular details of challenging biological systems. There have been several examples of applications including the study of protein assembly pathways11,12,13,14, studying protein-protein interaction networks15,16,17, membrane proteins6,18,19,20,21, and protein-ligand interactions such as nucleic acids22,23,24.
However, native MS also has its limitations. Native MS measurements are often performed in volatile buffers such as aqueous ammonium acetate in which some proteins will not retain their folded native state3,25. Nevertheless, recent work has shown that this limitation can be overcome by optimization of spraying needle tip diameter (0.5 mm tips) such that protein and protein complex ions can be formed directly from non-volatile buffers with high-ionic-strength that better mimic the physiological environment26. Additionally, native MS uses electrospray to ionize and transfer non-covalent assemblies from solution to the gas phase; therefore, the relative abundance of detected complexes may not wholly represent that in solution5,27. Moreover, in comparison to in solution, the gas phase hydrophobic interactions become weaker and electrostatic interactions become stronger and hence favored3,28.
In this article, we provide protocols, data analysis, and interpretation for protein identification and ligand binding using native MS, IM-MS, CIU, in-solution disruption, and modelling. The DNA repair complex, HerA-NurA, is used as a model system. DNA double-stranded breaks (DSBs) are one of the most cytotoxic and deleterious forms of DNA damage, resulting in genetic instability and the eventual development of cancer in humans. Homologous recombination is the repair mechanism which eradicates DSBs, a process which is orchestrated by the ATP dependent helicase-nuclease complex, HerA-NurA22.
Combining native MS and IM-MS with functional assays and modelling allowed the investigation of: i) the role of NurA in the assembly, conformation, and stability of the complex, ii) the interaction between dsDNA and the complex and its influence on the overall stability of the complex, and iii) the stoichiometry and impact of ATP binding on the assembly22. Overall, this work led to an improved understanding of the molecular basis of the HerA-NurA complex by linking protein complex conformational changes and stability with nucleotide binding. This protocol is generic for any protein complex(es) which interacts with one or several ligand(s) types.

<table border="0" cellpadding="0" cellspacing="0" style="width:572px;" width="573">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="60">
			<td height="60" style="height:60px;width:216px;">Adenosine 5&#8242;-(3-thiotriphosphate) tetralithium salt</td>
			<td style="width:71px;">Merck Millipore</td>
			<td style="width:119px;">119120-25MG</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Adenosine 5&#8242;-diphosphate&#160;</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">20398-34-9</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Ammonium acetate solution</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">A2706</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Micro Bio-Spin Chromatography Columns</td>
			<td style="width:71px;">Bio-Rad</td>
			<td style="width:119px;">7326204</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Vivaspin concentrator</td>
			<td style="width:71px;">Sartorius</td>
			<td style="width:119px;">Z614041-25EA</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Magnesium chloride hexahydrate</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">246964</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Water TraceSelect</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">95305</td>
			<td></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:216px;">Borosilicate Capillaries</td>
			<td style="width:71px;">Harvard Apparatus</td>
			<td style="width:119px;">300060</td>
			<td></td>
		</tr>
	</tbody>
</table>

analyzing protein architectures and protein-ligand complexes by integrative structural mass spectrometry

Proteins are an important class of biological macromolecules that play many key roles in cellular functions including gene expression, catalyzing metabolic reactions, DNA repair and replication. Therefore, a detailed understanding of these processes provides critical information on how cells function. Integrative structural MS methods offer structural and dynamical information on protein complex assembly, complex connectivity, subunit stoichiometry, protein oligomerization and ligand binding. Recent advances in integrative structural MS have allowed for the characterization of challenging biological systems including large DNA binding proteins and membrane proteins. This protocol describes how to integrate diverse MS data such as native MS and ion mobility-mass spectrometry (IM-MS) with molecular dynamics simulations to gain insights into a helicase-nuclease DNA repair protein complex. The resulting approach provides a framework for detailed studies of ligand binding to other protein complexes involved in important biological processes.

Native MS results revealed the oligomeric state, composition and topology of the HerA-NurA complex (Figure 1). As non-covalent interactions are preserved in the gas-phase, native MS of ATP-&#947;-S and ADP titrations experiments determined the pairwise nucleotide binding to HerA-NurA (Figure 2) and that increasing the ATP-&#947;-S concentration increases the relative intensity of hexameric HerA (Figure 3). Structural information regarding subunit interactions were obtained from in-solution disruption followed by native MS and were in agreement with and theoretical masses (Figure 4 and Table 1).
The experimental CCS values of proteins and their complexes was derived from IM-MS experiments (Figure 5). These values are rotationally averaged gas-phase cross-sectional calculations of the molecular shape, and describe the dimensional state of the protein. CCS values are compared to theoretical measurements from x-ray crystallography and a good agreement infers that the native shape in retained in the gas-phase (Table 1). This validates using CCS values for building low-resolution models of the protein assembly48.
Experimental CCSs can be calculated for each charge state ion. A native-like protein conformer may give rise to charge state ions with similar CCS values. However, higher charge state ions increased coulombic repulsions which may lead to protein gas-phase unfolding and larger CCS values compared to the theoretical CCSs. The CCS value of the lowest charge state ions are therefore usually used49. For HerA-NurA, in-solution disruption experiments on HerA and HerA-NurA with and without DNA prompted the generation of an assembly pathway starting with monomers then forming the entire hexameric HerA (HerA6)-dimeric NurA (NurA2) complex with DNA (Figure 6).
Differences in the CIU unfolding plots between the apo (ligand-free) and ligand bound define the change in complex stability upon ligand binding. A higher CV50 or KECOM value implies a more stabilized ion in the gas-phase. CIU and KECOM analysis revealed DNA-bound HerA-NurA is more stable than the DNA-free complex (Figure 7Aii). From CIU-MS analysis in the respective ATP-binding states, the four-ATP-&#947;-S bound state reduced complex stability in the gas-phase and the six -ATP-&#947;-S bound state where are all sites are occupied was the most stable (Figure 7Bii). Native MS can reveal the discrete nucleotide binding states of HerA; however, it cannot distinguish which HerA subunits are binding ATP and where this binding takes place. This information can be derived from explicit solvent MD simulations on the hexameric HerA and the HerA-NurA following the summarised Workflow (Figure 8).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57966/57966fig1.jpg" /> 
Figure 1. Interrogating the oligomeric state, composition and topology of the HerA-NurA non-covalent complex. (A) Mass spectra of HerA, HerA-NurA and HerA-NurA in the presence of DNA (15.4 kDa 25 bp double- stranded DNA). The HerA sub-complex exists as both a hexamer and a heptamer. NurA dimer binds and to a HerA hexamer imposing oligomeric conversion. The DNA binds the formed HerA- NurA complex (Results adapted from Z. Ahdash et al., 201722). (B) Relative intensities of the identified species are calculated using UniDec32. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57966/57966fig2.jpg" /> 
Figure 2. Native ESI-MS reveals the mechanism of nucleotide binding to HerA-NurA. Mass spectra (A) HerA-NurA and (B) HerA-NurA-DNA with increasing concentrations of (i) ATP-&#947;-S and (ii) ADP. Measured masses are compared to theoretical masses and the amount of ATP-&#947;-S or ADP bound are determined. Measured masses and number of bound nucleotides are shown on the spectra. ATP-&#947;-S and ADP titrations experiments determined the pairwise nucleotide binding to HerA-NurA alone and when in complex with DNA indicating a cyclical reaction mechanism (Results adapted from Z. Ahdash et al., 201722). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57966/57966fig3.jpg" /> 
Figure 3. Measuring the effect of increasing ATP-&#947;-S concentrations on HerA oligomeric state. (A) Mass spectra of HerA at increasing concentrations of ATP-&#947;-S. (B) Graph showing the relative intensities of different species from native MS calculated using UniDec deconvolution software32. As the ATP-&#947;-S concentration increases, the relative intensity of hexameric HerA also increases. Number of ATP-&#947;-S molecules bound is shown on the spectra (Results adapted from Z. Ahdash et al., 201722). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/57966/57966fig4.jpg" /> 
Figure 4. Mass spectra and sub-complex dissociation products of (A) HerA and (B) HerA-NurA (i) alone and in the presence of (ii) DNA following of in-solution disruption. In-solution disruption experiments were performed using 10-40% of Acetonitrile, Methanol (MeOH) or dimethyl sulfoxide (DMSO) and resulted in the formation of various subcomplexes. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57966/57966fig5.jpg" /> 
Figure 5. Ion mobility arrival time distributions shown on a CCS axis for complexes and generated sub-complexes. Icon for each sub-complex correlate with those annotated on the spectra in Figure 4. Experimental and calculated masses and CCS values of Sub-complexes are listed in Table 1 all of which showed an agreement between experimental and calculated values (after considering the typical uncertainty in the resolution of travelling wave ion mobility mass spectrometry of &#177;5-8%37). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57966/57966fig6.jpg" /> 
Figure 6. Assembly pathway of the HerA-NurA complex generated from in-solution disruption native MS and IM-MS. Colored circles indicate conditions where each sub-complex was observed: native (green, prior to disruption), Methanol (yellow), DMSO (purple) or Acetonitrile (red). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/57966/57966fig7.jpg" /> 
Figure 7. Investigating the stabilizing effect of (A) DNA on HerA-NurA and (B) ATP binding to HerA-NurA-DNA. (i) Gas-phase CIU-MS plots and (ii) center-of-mass collision energies (KEcom) calculation show that that the presence of dsDNA stabilizes the HerA-NurA complex and that the six ATP-&#947;-S bound state is the most stable. Stabilization for different charge states is shown. Plots were generated using PULSAR 33. Results from (A) adapted from Z. Ahdash et al., 201722. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/57966/57966fig8.jpg" /> 
Figure 8. Workflow for the modelling procedures for differential molecular dynamics simulations. (A) Generating the complex under investigation by building the topology from existing subunits and rebuilding missing residues. (B) Workflow for running molecular dynamics simulations on the protein complex with and without ligand. Molecular dynamics simulations are ran for the protein only which acts as a reference and which is subtracted from simulation of protein plus ligand. This is followed by calculating the differential root mean square fluctuation (RMSF) between the simulations and determining the effect of ligand binding. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57966/57966fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Complex&#160; / sub-complex</td>
			<td>Theoretical&#160; Mass (kDa)</td>
			<td>Experimental&#160; Mass (kDa)</td>
			<td>Theoretical CCS (&#197;2)</td>
			<td>Experimental CCS (&#197;2) [charge]</td>
			<td>Condition HN</td>
		</tr>
		<tr>
			<td>HerA6-NurA2</td>
			<td>416.22</td>
			<td>417.85</td>
			<td>14531</td>
			<td>14577 [42+] 
			14599 [43+] 
			14608 [44+] 
			14637 [45+]</td>
			<td>10-20% ACN, 10-40% DMSO, 10% MeOH</td>
		</tr>
		<tr>
			<td>HerA6-NurA2-dsDNA</td>
			<td>431.72</td>
			<td>432.27</td>
			<td>-</td>
			<td>14661 [39+] 
			14728 [40+] 
			14781 [41+] 
			14837 [42+]</td>
			<td>10% ACN, 10% MeOH</td>
		</tr>
		<tr>
			<td>NurA1</td>
			<td>39.12</td>
			<td>38.18</td>
			<td>3254</td>
			<td>2618 [10+] 
			2746 [11+] 
			2878 [12+]</td>
			<td>10-40% ACN, 10% MeOH, 20-40% DMSO</td>
		</tr>
		<tr>
			<td>NurA2</td>
			<td>78.24</td>
			<td>78.36</td>
			<td>4890</td>
			<td>4903 [16+] 
			4614 [17+] 
			4537 [18+] 
			4666 [19+]</td>
			<td>10-40% MeOH, 20-40% DMSO</td>
		</tr>
		<tr>
			<td>HerA1</td>
			<td>56.33</td>
			<td>56.32</td>
			<td>4131</td>
			<td>3647 [14+] 
			3792 [15+] 
			3950 [16+]</td>
			<td>10-40% ACN, 40% DMSO</td>
		</tr>
		<tr>
			<td>HerA2</td>
			<td>112.66</td>
			<td>112.95</td>
			<td>6475</td>
			<td>5648 [20+] 
			5747 [21+] 
			5842 [22+] 
			5996 [23+]</td>
			<td>40% Meth, 10-40% ACN</td>
		</tr>
		<tr>
			<td>HerA3</td>
			<td>168.99</td>
			<td>169.39</td>
			<td>8607</td>
			<td>7501 [25+] 
			7616 [26+] 
			7717 [27+] 
			7867 [28+]</td>
			<td>10-40% MeOH, 10-40% CAN, 40% DMSO</td>
		</tr>
		<tr>
			<td>HerA3 + DNA</td>
			<td>183.99</td>
			<td>184.976</td>
			<td>-</td>
			<td>7655 [26+] 
			7990 [27+] 
			8107 [28+]</td>
			<td>10-30% ACN</td>
		</tr>
		<tr>
			<td>HerA4</td>
			<td>225.32</td>
			<td>226.2</td>
			<td>10477</td>
			<td>9205 [30+] 
			9287 [31] 
			9493 [32+] 
			9961 [33+]</td>
			<td>10-40% MeOH, 10-40% ACN</td>
		</tr>
		<tr>
			<td>HerA4 +DNA</td>
			<td>240.82</td>
			<td>241.33</td>
			<td>-</td>
			<td>9637 [31+] 
			9756 [32+] 
			9830 [33+]</td>
			<td>10-30% ACN</td>
		</tr>
		<tr>
			<td>HerA5</td>
			<td>281.65</td>
			<td>282.75</td>
			<td>11853</td>
			<td>10847 [36+] 
			10958 [37+] 
			11161 [38+]</td>
			<td>30-40% ACN</td>
		</tr>
		<tr>
			<td>HerA6</td>
			<td>337.98</td>
			<td>339.3</td>
			<td>12517</td>
			<td>12335 [38+] 
			12386 [39+] 
			12498 [40+] 
			12590 [41+] 
			12676 [42+] 
			13019 [43+]</td>
			<td>10-40% MeOH, 10-40% ACN</td>
		</tr>
		<tr>
			<td>HerA6 +DNA</td>
			<td>353.48</td>
			<td>354.626</td>
			<td>-</td>
			<td>12890 [40+] 
			13081 [41+] 
			13184 [42+] 
			13273 [43+] 
			13463 [44+] 
			13576 [45+]</td>
			<td>30% ACN</td>
		</tr>
		<tr>
			<td>HerA7</td>
			<td>394.3</td>
			<td>395.85</td>
			<td>13901</td>
			<td>14154 [42+] 
			14219 [43+] 
			14261 [44+] 
			14285 [45+] 
			14335 [46+]</td>
			<td>10-40% MeOH, 10-40% ACN, 10-40% DMSO</td>
		</tr>
		<tr>
			<td>HerA7 +DNA</td>
			<td>409.8</td>
			<td>410.62</td>
			<td>-</td>
			<td>14414 [41+] 
			14510 [42+] 
			14558 [43+] 
			14598 [44+] 
			14630 [45+] 
			14641 [46+]</td>
			<td>10% ACN</td>
		</tr>
	</tbody>
</table>
Table 1. Experimental and calculated masses and CCS values of HerA-NurA and its sub-complexes generated form in-solution disruption studies.

Watch this Scientific Journal Video about Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry at JoVE.com

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry | Chemistry | Video

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Mass spectrometry (MS) has emerged as an important tool for the investigation of structure and dynamics of macromolecular assemblies. Here, we integrate MS-based approaches to interrogate protein complex formation and ligand binding.

Proteins are an important class of biological macromolecules that play many key roles in cellular functions including gene expression, catalyzing ...

analyzing-protein-architectures-protein-ligand-complexes-integrative

Nanyang Technological University

Education

Research

JoVE Core

JoVE Journal

Cell Biology

Chemistry

Biology

Molecular Biology

Unit 1

Fundamentals

Protein Function

Macromolecules

SCIENTISTS IN ACTION

14.1K Views.  King's College London. Mass spectrometry (MS) has emerged as an important tool for the investigation of structure and dynamics of macromolecular assemblies. Here, we integrate MS-based approaches to interrogate protein complex formation and ligand binding.

Video: Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Production of Disulfide-stabilized Transmembrane Peptide Complexes for Structural Studies

Physical interactions among the lipid-embedded alpha-helical domains of membrane proteins play a crucial role in folding and assembly of membrane protein complexes and in dynamic processes such as transmembrane (TM) signaling and regulation of cell-surface protein levels. Understanding the structural features driving the association of particular sequences requires sophisticated biophysical and biochemical analyses of TM peptide complexes. However, the extreme hydrophobicity of TM domains makes them very difficult to manipulate using standard peptide chemistry techniques, and production of suitable study material often proves prohibitively challenging. Identifying conditions under which peptides can adopt stable helical conformations and form complexes spontaneously adds a further level of difficulty. Here we present a procedure for the production of homo- or hetero-dimeric TM peptide complexes from materials that are expressed in E. coli, thus allowing incorporation of stable isotope labels for nuclear magnetic resonance (NMR) or non-natural amino acids for other applications relatively inexpensively. The key innovation in this method is that TM complexes are produced and purified as covalently associated (disulfide-crosslinked) assemblies that can form stable, stoichiometric and homogeneous structures when reconstituted into detergent, lipid or other membrane-mimetic materials. We also present carefully optimized procedures for expression and purification that are equally applicable whether producing single TM domains or crosslinked complexes and provide advice for adapting these methods to new TM sequences.

Biophysical and biochemical studies of interactions among membrane-embedded protein domains face many technical challenges, the first of which is obtaining appropriate study material. This article describes a protocol for producing and purifying disulfide-stabilized transmembrane peptide complexes that are suitable for structural analysis by solution nuclear magnetic resonance (NMR) and other analytical applications.

Physical  interactions among the lipid-embedded alpha-helical domains of membrane  proteins play a crucial role in folding and assembly of membrane ...

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox reactions. The Cu (I) complex of the peptide model of a Cu (I) binding metallochaperone protein, which includes the sequence MTCSGCSRPG (underlined is conserved), was determined in solution under inert conditions by NMR spectroscopy.
NMR is a widely accepted technique for the determination of solution structures of proteins and peptides. Due to difficulty in crystallization to provide single crystals suitable for X-ray crystallography, the NMR technique is extremely valuable, especially as it provides information on the solution state rather than the solid state. Herein we describe all steps that are required for full three-dimensional structure determinations by NMR. The protocol includes sample preparation in an NMR tube, 1D and 2D data collection and processing, peak assignment and integration, molecular mechanics calculations, and structure analysis. Importantly, the analysis was first conducted without any preset metal-ligand bonds, to assure a reliable structure determination in an unbiased manner.

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

The NMR-solution structure of a metallochaperone model peptide with Cu (I) was determined, and a detailed protocol from sample preparation and 1D and 2D data collection to a three-dimensional structure is described.

Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox ...

Analyzing Protein Dynamics Using Hydrogen Exchange Mass Spectrometry

All cellular processes depend on the functionality of proteins. Although the functionality of a given protein is the direct consequence of its unique amino acid sequence, it is only realized by the folding of the polypeptide chain into a single defined three-dimensional arrangement or more commonly into an ensemble of interconverting conformations. Investigating the connection between protein conformation and its function is therefore essential for a complete understanding of how proteins are able to fulfill their great variety of tasks. One possibility to study conformational changes a protein undergoes while progressing through its functional cycle is hydrogen-1H/2H-exchange in combination with high-resolution mass spectrometry (HX-MS). HX-MS is a versatile and robust method that adds a new dimension to structural information obtained by e.g. crystallography. It is used to study protein folding and unfolding, binding of small molecule ligands, protein-protein interactions, conformational changes linked to enzyme catalysis, and allostery. In addition, HX-MS is often used when the amount of protein is very limited or crystallization of the protein is not feasible. Here we provide a general protocol for studying protein dynamics with HX-MS and describe as an example how to reveal the interaction interface of two proteins in a complex. &#160;&#160;

Protein conformation and dynamics are key to understanding the relationship between protein structure and function. Hydrogen exchange coupled with high-resolution mass spectrometry is a versatile method to study the conformational dynamics of proteins as well as characterizing protein-ligand and protein-protein interactions, including contact interfaces and allosteric effects.

All cellular processes depend on the functionality of proteins. Although the functionality of a given protein is the direct consequence of its unique ...

Improved In-gel Reductive &#946;-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry

Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of biological samples. Similar approaches, that would allow in-depth analysis of the glycans carried by glycoproteins resolved by SDS-PAGE, require special considerations in order to maximize recovery and sensitivity when using mass spectrometry (MS) as the detection method. A major hurdle to be overcome in achieving high-quality data is the removal of gel-derived contaminants that interfere with MS analysis. The sample workflow presented here is robust, efficient, and eliminates the need for in-line HPLC clean-up prior to MS. Gel pieces containing target proteins are washed in acetonitrile, water, and ethyl acetate to remove contaminants, including polymeric acrylamide fragments. O-linked glycans are released from target proteins by in-gel reductive &#946;-elimination and recovered through robust, simple clean-up procedures. An advantage of this workflow is that it improves sensitivity for detecting and characterizing sulfated glycans. These procedures produce an efficient separation of sulfated permethylated glycans from non-sulfated (sialylated and neutral) permethylated glycans by a rapid phase-partition prior to MS analysis, and thereby enhance glycomic and sulfoglycomic analyses of glycoproteins resolved by SDS-PAGE.

In order to comprehensively explore the diversity of O-linked glycans, a new procedure for in-gel reductive &#946;-elimination, combined with permethylation and a rapid phase-partition method, is applied to the analysis of O-linked glycans directly released from glycoproteins resolved by SDS-PAGE and amenable to subsequent glycomic analysis by mass spectrometry.

Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of ...

Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry

Exhaled volatile organic compounds (VOCs) have aroused considerable interest, since they can serve as biomarkers for disease diagnosis and environmental exposure in a non-invasive manner. In this work, we present a protocol to characterize the exhaled VOCs in real time by using secondary nanoelectrospray ionization coupled to high resolution mass spectrometry (Sec-nanoESI-HRMS). The homemade Sec-nanoESI source was readily set up based on a commercial nanoESI source. Hundreds of peaks were observed in the background-subtracted mass spectra of exhaled breath, and the mass accuracy values are -4.0-13.5 ppm and -20.3-1.3 ppm in the positive and negative ion detection modes, respectively. The peaks were assigned with accurate elemental composition according to the accurate mass and isotopic pattern. Less than 30 s is used for one exhalation measurement, and it takes approximately 7 min for six replicated measurements.

A protocol for characterizing chemical composition of exhaled breath in real time by using secondary nanoelectrospray ionization coupled to high resolution mass spectrometry is demonstrated.

Exhaled volatile organic compounds (VOCs) have aroused considerable interest, since they can serve as biomarkers for disease diagnosis and environmental ...

Synthesis and Mass Spectrometry Analysis of Oligo-peptoids

Peptoids are sequence-controlled peptide-mimicking oligomers consisting of N-alkylated glycine units. Among many potential applications, peptoids have been thought of as a type of molecular information storage. Mass spectrometry analysis has been considered the method of choice for sequencing peptoids. Peptoids can be synthesized via solid phase chemistry using a repeating two-step reaction cycle. Here we present a method to manually synthesize oligo-peptoids and to analyze the sequence of the peptoids using tandem mass spectrometry (MS/MS) techniques. The sample peptoid is a nonamer consisting of alternating N-(2-methyloxyethyl)glycine (Nme) and N-(2-phenylethyl)glycine (Npe), as well as an N-(2-aminoethyl)glycine (Nae) at the N-terminus. The sequence formula of the peptoid is Ac-Nae-(Npe-Nme)4-NH2, where Ac is the acetyl group. The synthesis takes place in a commercially available solid-phase reaction vessel. The rink amide resin is used as the solid support to yield the peptoid with an amide group at the C-terminus. The resulting peptoid product is subjected to sequence analysis using a triple-quadrupole mass spectrometer coupled to an electrospray ionization source. The MS/MS measurement produces a spectrum of fragment ions resulting from the dissociation of charged peptoid. The fragment ions are sorted out based on the values of their mass-to-charge ratio (m/z). The m/z values of the fragment ions are compared against the nominal masses of theoretically predicted fragment ions, according to the scheme of peptoid fragmentation. The analysis generates a fragmentation pattern of the charged peptoid. The fragmentation pattern is correlated to the monomer sequence of the neutral peptoid. In this regard, MS analysis reads out the sequence information of the peptoids.

A protocol is described for the manual synthesis of oligo-peptoids followed by sequence analysis by mass spectrometry.

Peptoids are sequence-controlled peptide-mimicking oligomers consisting of N-alkylated glycine units. Among many potential applications, peptoids have ...

Capillary Electrophoresis Mass Spectrometry Approaches for Characterization of the Protein and Metabolite Corona Acquired by Nanomaterials

The adsorption of biomolecules from surrounding biological matrices to the surface of nanomaterials (NMs) to form the corona has been of interest for the past decade. Interest in the bio-nano interface arises from the fact that the biomolecular corona confers a biological identity to NMs and thus causes the body to identify them as &#8220;self&#8221;. For example, previous studies have demonstrated that the proteins in the corona are capable of interacting with membrane receptors to influence cellular uptake and established that the corona is responsible for cellular trafficking of NMs and their eventual toxicity. To date, most research has focused upon the protein corona and overlooked the possible impacts of the metabolites included in the corona or synergistic effects between components in the complete biomolecular corona. As such, this work demonstrates methodologies to characterize both the protein and metabolite components of the biomolecular corona using bottom-up proteomics and metabolomics approaches in parallel. This includes an on-particle digest of the protein corona with a surfactant used to increase protein recovery, and a passive characterization of the metabolite corona by analyzing metabolite matrices before and after NM exposures. This work introduces capillary electrophoresis &#8211; mass spectrometry (CESI-MS) as a new technique for NM corona characterization. The protocols outlined here demonstrate how CESI-MS can be used for the reliable characterization of both the protein and metabolite corona acquired by NMs. The move to CESI-MS greatly decreases the volume of sample required (compared to traditional liquid chromatography &#8211; mass spectrometry (LC-MS) approaches) with multiple injections possible from as little as 5 &#181;L of sample, making it ideal for volume limited samples. Furthermore, the environmental consequences of analysis are reduced with respect to LC-MS due to the low flow rates (&#60;20 nL/min) in CESI-MS, and the use of aqueous electrolytes which eliminates the need for organic solvents.

Here we present a protocol to characterize the complete biomolecular corona, proteins, and metabolites, acquired by nanomaterials from biofluids using a capillary electrophoresis &#8211; mass spectrometry approach.

The adsorption of biomolecules from surrounding biological matrices to the surface of nanomaterials (NMs) to form the corona has been of interest for the ...

Covalent Labeling with Diethylpyrocarbonate for Studying Protein Higher-Order Structure by Mass Spectrometry

Characterizing a protein&#39;s higher-order structure is essential for understanding its function. Mass spectrometry (MS) has emerged as a powerful tool for this purpose, especially for protein systems that are difficult to study by traditional methods. To study a protein&#39;s structure by MS, specific chemical reactions are performed in solution that encode a protein&#39;s structural information into its mass. One particularly effective approach is to use reagents that covalently modify solvent accessible amino acid side chains. These reactions lead to mass increases that can be localized with residue-level resolution when combined with proteolytic digestion and tandem mass spectrometry. Here, we describe the protocols associated with use of diethylpyrocarbonate (DEPC) as a covalent labeling reagent together with MS detection. DEPC is a highly electrophilic molecule capable of labeling up to 30% of the residues in the average protein, thereby providing excellent structural resolution. DEPC has been successfully used together with MS to obtain structural information for small single-domain proteins, such as &#946;2-microglobulin, to large multi-domain proteins, such as monoclonal antibodies.

The experimental procedures for performing diethylpyrocarbonate-based covalent labeling with mass spectrometric detection are described. Diethylpyrocarbonate is simply mixed with the protein or protein complex of interest, leading to the modification of solvent accessible amino acid residues. The modified residues can be identified after proteolytic digestion and liquid chromatography/mass spectrometry analysis.

Characterizing a protein&#39;s higher-order structure is essential for understanding its function. Mass spectrometry (MS) has emerged as a powerful tool ...

Monitoring Protein-Ligand Interactions in Human Cells by Real-Time Quantitative In-Cell NMR using a High Cell Density Bioreactor

In-cell NMR is a unique approach to observe the structural and dynamic properties of biological macromolecules at atomic resolution directly in living cells. Protein folding, chemical modifications, and conformational changes induced by ligand binding can be observed. Therefore, this method has great potential in the context of drug development. However, the short lifetime of human cells confined in the NMR spectrometer limits the application range of in-cell NMR. To overcome this issue, NMR bioreactors are employed that can greatly improve the cell sample stability over time and, importantly, enable the real-time recording of in-cell NMR spectra. In this way, the evolution of processes such as ligand penetration and binding to the intracellular protein target can be monitored in real time. Bioreactors are often limited by low cell viability at high cell numbers, which results in a trade-off between the overall sensitivity of the experiment and cell viability. We recently reported an NMR bioreactor that maintains a high number of human cells metabolically active for extended periods of time, up to 72 h. This setup was applied to monitor protein-ligand interactions and protein chemical modification. We also introduced a workflow for quantitative analysis of the real-time NMR data, based on multivariate curve resolution. The method provides concentration profiles of the chemical species present in the cells as a function of time, which can be further analyzed to obtain relevant kinetic parameters. Here we provide a detailed description of the NMR bioreactor setup and its application to monitoring protein-ligand interactions in human cells.

This protocol describes the setup of an NMR bioreactor to keep encapsulated human cells viable for up to 72 h, followed by time-resolved in-cell NMR data acquisition and analysis. The methodology is applied to monitor intracellular protein-ligand interactions in real time.

In-cell NMR is a unique approach to observe the structural and dynamic properties of biological macromolecules at atomic resolution directly in living ...

Organic Solvent-Based Protein Precipitation for Robust Proteome Purification Ahead of Mass Spectrometry

While multiple advances in mass spectrometry (MS) instruments have improved qualitative and quantitative proteome analysis, more reliable front-end approaches to isolate, enrich, and process proteins ahead of MS are critical for successful proteome characterization. Low, inconsistent protein recovery and residual impurities such as surfactants are detrimental to MS analysis. Protein precipitation is often considered unreliable, time-consuming, and technically challenging to perform compared to other sample preparation strategies. These concerns are overcome by employing optimal protein precipitation protocols. For acetone precipitation, the combination of specific salts, temperature control, solvent composition, and precipitation time is critical, while the efficiency of chloroform/methanol/water precipitation depends on proper pipetting and vial manipulation. Alternatively, these precipitation protocols are streamlined and semi-automated within a disposable spin cartridge. The expected outcomes of solvent-based protein precipitation in the conventional format and using a disposable, two-stage filtration and extraction cartridge are illustrated in this work. This includes the detailed characterization of proteomic mixtures by bottom-up LC-MS/MS analysis. The superior performance of SDS-based workflows is also demonstrated relative to non-contaminated protein.

The present protocol describes solvent-based protein precipitation under controlled conditions for robust and rapid recovery and purification of proteome samples prior to mass spectrometry.

While multiple advances in mass spectrometry (MS) instruments have improved qualitative and quantitative proteome analysis, more reliable front-end ...