Chemistry
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Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry
Chapters
Summary October 15th, 2018
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.
Transcript
Nowadays mass spectrometry plays an important role in structural biology. This method can help answer key questions about important biological macromolecules in their native state, especially proteins and protein complexes. Native mass spectrometry is widely applicable to a variety of biomolecular assemblies including multiprotein and nucleic acid systems.
The main advantage of this technique is that it's rapid and highly sensitive. It can be used to interrogate heterogeneous protein samples, make it possible to analyze multiple proteins in oligomeric state simultaneously. Demonstrating the procedure will be Andy Lau, a PhD student in my group.
To begin this procedure, prepare the in-house capillaries for nanoelectrospray as outlined in the text protocol. Prepare a ligand-free sample as a control for each run as buffer exchange each into ammonium acetate. Next, select the sensitivity, positive ion acquisition, and mobility TOF modes.
Next turn on the trap, API, and IMS gases. For IM separation use the nitrogen and argon starting points shown here and adjust as necessary. Set an appropriate m/z acquisition range.
For an unknown protein the initial optimization steps should use a wide range. Insert the gold-coated capillary into a capillary holder. Then load between two and three microliters of the protein complex solution of interest into the capillary.
Gently tighten the capillary and place it on the electrospray source stage. Slide the stage into position to start acquiring data. Apply a low nano-flow gas pressure until a drop forms at the tip of the capillary.
Move the capillary with respect to the cone and monitor the ion current to achieve a stable ion current. Apply a capillary voltage in the range between 0.9 and 1.6 kilovolts. Then set the sampling cone, source offset, source temperature, and cone gas flow as outlined in the text protocol.
To acquire a well resolved mass spectrum and maximized ion transmission, adjust the MS parameters and monitor the resulting change in the spectra. Set the trap collision energy to an initial starting point between 10 and 50 volts. If the voltage offsets are insufficient, adjust the trap collision energies.
Set the trap via its voltage to an initial starting point between 20 and 45 volts. Improve desolvation by optimizing this voltage. After this, optimize the wave velocity and wave height as outlined in the text to achieve the best mobility separation.
For studies involving HerA and NurA use a wave velocity of 40 meters per second and a wave height between 550 and 650 volts. For DNA binding analysis, mix the protein and DNA at a molar ratio that allows for protein DNA complex formation. Add increasing amounts of any of the following, 5'O-3-thio-triphosphate, tetralithium salt, or ADP.
Using appropriate software measure the masses of generated species and identify the ligand binding, such as ATP and ADP binding and oligomeric states. Then use the ion intensities observed in the raw ESI MS spectra to quantify the corresponding relative abundance of species. After optimizing the instrument conditions for stable transmission, reduce the collisional energy and sampling cone as low as possible, while still retaining good spectra quality.
Use the previously determined optimized wave velocity and wave height to acquire IM MS.Measure the ion drift time at three different wave velocities while maintaining the same wave height. To determine the protein ion CCS measure four protein calibrants, two with the mass above the protein under investigation and two with the mass below, using the same instrumentation conditions. First, prepare the protein samples and buffer exchange them into ammonium acetate as outlined in the text protocol.
Add solvent in 10%increments until reaching the desired amount. Incubate on ice for one hour. After this, acquire an IM-MS spectrum for each sample.
Using the SUMMIT software, assign protein subcomplexes and generate protein interaction networks. Alternatively, manually generate a list of theoretical masses for the expected species. To begin investigating protein complex stability, record IM-MS data while increasing the trap acceleration voltage from 10 volts to 200 volts, which will progressively unfold to the protein and the gas phase.
Analyze the data using appropriate software and generate two-dimensional unfolding plots by stacking the intensity normalized CCS distributions at each accelerating voltage for each charge state. Native MS results reveal the oligomeric state, composition, and topology of the HerA and NurA complex. As noncovalent interactions are preserved in the gas phase, native MS of ATP gamma S and ADP titration experiments, are used to determine the pair-wise nucleotide binding in the HerA and NurA.
Mass spectra of the HerA oligomeric states reveal that increasing the ATP gamma S concentration increases the relative intensity of hexameric HerA. The experimental CCS values for the proteins and their complexes are then derived from the IM-MS experiments. These values are seen to have good agreement with theoretical measurements from x-ray crystallography, which validates using CCS values for building low-resolution models of protein assembly.
CIU and KEcom analysis reveals that DNA bound HerA-NurA is more stable than the DNA-free complex. CIU MS analysis and the respective ATP binding states shows that the four ATP gamma S bound state reduces complex stability in the gas phase. However, the six ATP gamma S bound state in which all sites are occupied, is seen to be the most stable.
Accurate measurements of the molecular mass of an intact complex provides valuable insight into biomolecular characterization. We can get information on complex assembly pathways, protein oligomerization, and ligand binding. Combining all this information allows to generate detailed models of functional biological assemblies.
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