One of the most challenging stress conditions that organisms encounter during their lifetime involves the accumulation of oxidants. During oxidative stress, cells heavily rely on molecular chaperones. Here, we present methods used to investigate the redox-regulated anti-aggregation activity, as well as to monitor structural changes governing the chaperone function using HDX-MS.
Living organisms regularly need to cope with fluctuating environments during their life cycle, including changes in temperature, pH, the accumulation of reactive oxygen species, and more. These fluctuations can lead to a widespread protein unfolding, aggregation, and cell death. Therefore, cells have evolved a dynamic and stress-specific network of molecular chaperones, which maintain a “healthy” proteome during stress conditions. ATP-independent chaperones constitute one major class of molecular chaperones, which serve as first-line defense molecules, protecting against protein aggregation in a stress-dependent manner. One feature these chaperones have in common is their ability to utilize structural plasticity for their stress-specific activation, recognition, and release of the misfolded client.
In this paper, we focus on the functional and structural analysis of one such intrinsically disordered chaperone, the bacterial redox-regulated Hsp33, which protects proteins against aggregation during oxidative stress. Here, we present a toolbox of diverse techniques for studying redox-regulated chaperone activity, as well as for mapping conformational changes of the chaperone, underlying its activity. Specifically, we describe a workflow which includes the preparation of fully reduced and fully oxidized proteins, followed by an analysis of the chaperone anti-aggregation activity in vitro using light-scattering, focusing on the degree of the anti-aggregation activity and its kinetics. To overcome frequent outliers accumulated during aggregation assays, we describe the usage of Kfits, a novel graphical tool which allows easy processing of kinetic measurements. This tool can be easily applied to other types of kinetic measurements for removing outliers and fitting kinetic parameters. To correlate the function with the protein structure, we describe the setup and workflow of a structural mass spectrometry technique, hydrogen-deuterium exchange mass spectrometry, that allows the mapping of conformational changes on the chaperone and substrate during different stages of Hsp33 activity. The same methodology can be applied to other protein-protein and protein-ligand interactions.
Cells frequently encounter an accumulation of reactive oxygen species (ROS) produced as byproducts of respiration1,2, protein and lipid oxidation3,4, and additional processes5,6,7. Despite ROS' beneficial role in diverse biological processes such as cellular signaling8,9 and immune response10, an imbalance between ROS production and its detoxification might occur, leading to oxidative stress7. The biological targets of ROS are proteins, lipids, and nucleic acids, the oxidation of which affect their structure and function. Therefore, the accumulation of cellular oxidants is strongly linked to a diverse range of pathologies including cancer9,11, inflammation12,13, and aging14,15, and have been found to be involved in the onset and progression of neurodegenerative disorders such as Alzheimer's, Parkinson's, and ALS disease16,17,18.
Both newly synthesized and mature proteins are highly sensitive to oxidation due to the potentially harmful modifications of their side chains, which shape protein structure and function19,20. Therefore, oxidative stress usually leads to a widespread protein inactivation, misfolding and aggregation, eventually leading to cell death. One of the elegant cellular strategies to cope with the potential damage of protein oxidation is to utilize redox-dependent chaperones, which inhibit the widespread protein aggregation, instead of forming stable complexes with misfolded client proteins21,22,23. These first-line defense chaperones are rapidly activated by a site-specific oxidation (usually on cysteine residues) that converts them into potent anti-aggregation molecules24. Since oxidative stress results in the inhibition of respiration and in decreases in the cellular ATP levels25, canonical ATP-dependent chaperones are less effective during oxidative stress conditions25,26,27. Therefore, redox-activated ATP-independent chaperones play a vital role in maintaining protein homeostasis upon the accumulation of oxidants in bacteria and eukaryotes (e.g., Hsp3328 and RidA29 in bacteria, Get330 in yeast, peroxiredoxins31 in eukaryotes). The activity of these chaperones strongly depends on reversible structural conformational changes induced by a site-specific oxidation that uncovers hydrophobic regions involved in the recognition of misfolded client proteins.
Research of the anti-aggregation mechanism and the principles governing the recognition of the client proteins by chaperones is not easy due to the dynamic and heterogenic nature of chaperone-substrate interactions32,33,34,35,36,37. However, stress-regulated chaperones have an opportunity to advance our understanding of the anti-aggregation function due to their ability to: 1) obtain two different forms of the chaperone, active (e.g., oxidized) and inactive (e.g., reduced), with the introduction or removal of a stress condition easily switching between them (e.g., oxidant and reducing agent), 2) have a broad range of substrates, 3) form highly stable complexes with the client proteins that may be evaluated by different structural methodologies, and 4) focus solely on the substrate recognition and release, mediated by redox-dependent conformational changes, as the majority of these chaperones lacks the folding capability.
Here, we analyze the bacterial redox-regulated chaperone Hsp33's anti-aggregation activity, a vital component of the bacterial defense system against oxidation-induced protein aggregation28. When reduced, Hsp33 is a tightly folded zinc-binding protein with no chaperone activity; however, when exposed to oxidative stress, Hsp33 undergoes extensive conformational changes which expose its substrate binding regions38,39. Upon oxidation, the zinc ion that is strongly bound to four highly conserved cysteine residues of the C-terminal domain is released40. This results in the formation of two disulfide bonds, an unfolding of the C-terminal domain, and a destabilization of the adjacent linker region41. The C-terminal and linker regions are highly flexible and are defined as intrinsically or partially disordered. Upon return to non-stress conditions, the cysteines become reduced and the chaperone returns to its native folded state with no anti-aggregation activity. The refolding of the chaperone leads to a further unfolding and destabilization of the bound client protein, which triggers its transfer to the canonical chaperone system, DnaK/J, for refolding38. Analysis of Hsp33's interaction sites suggests that Hsp33 uses both its charged disordered regions as well as the hydrophobic regions on the linker and N-terminal domain to capture misfolded client proteins and prevent their aggregation38,42. In the folded state, these regions are hidden by the folded linker and C-terminal domain. Interestingly, the linker region serves as a gatekeeper of Hsp33's folded and inactive state, "sensing" the folding status of its adjacent C-terminal domain34. Once destabilized by mutagenesis (either by a point mutation or a full sequence perturbation), Hsp33 is converted to a constitutively active chaperone regardless the redox state of its redox-sensitive cysteines43.
The protocols presented here allow monitoring of Hsp33's redox-dependent chaperone activity, as well as mapping conformational changes upon the activation and binding of client proteins. This methodology can be adapted to research other chaperone-client recognition models as well as non-chaperone protein-protein interactions. Moreover, we present protocols for the preparation of fully reduced and oxidized chaperones that can be used in studies of other redox-switch proteins, to reveal potential roles of protein oxidation on the protein activity.
Specifically, we describe a procedure to monitor chaperone activity in vitro and define its substrate specificity under different types of protein aggregation (chemically or thermally induced) using light scattering (LS) measured by a fluorospectrometer44. During aggregation, light scattering at 360 nm increases rapidly due to the increasing turbidity. Thus, aggregation can be monitored in a time-dependent manner at this wavelength. LS is a fast and sensitive method for testing protein aggregation and thus the anti-aggregation activity of a protein of interest using nanomolar concentrations, enabling the characterization of protein aggregation-related kinetic parameters under different conditions. Moreover, the LS protocol described here does not require expensive instrumentation, and can be easily established in any laboratory.
Nevertheless, it is quite challenging to obtain "clean" kinetic curves and to derive a protein's kinetic parameters from such light scattering experiments, due to noise and the large number of outliers generated by air bubbles and large aggregates. To overcome this obstacle, we present a novel graphical tool, Kfits45, used for reducing noise levels in different kinetic measurements, specifically fitted for protein aggregation kinetic data. This software provides preliminary kinetic parameters for an early assessment of the results and allows the user to "clean" large quantities of data quickly without affecting its kinetic properties. Kfits is implemented in Python and available in open source at 45.
One of the challenging questions in the field relates to mapping interaction sites between chaperones and their client proteins and understanding how chaperones recognize a wide range of misfolded substrates. This question is further complicated when studying highly dynamic protein complexes which involve intrinsically disordered chaperones and aggregation-prone substrates. Fortunately, structural mass spectrometry has dramatically advanced over the last decade and has successfully provided helpful approaches and tools to analyze the structural plasticity and map residues involved in protein recognition46,47,48,49. Here, we present one such technique-hydrogen-deuterium exchange mass spectrometry (HDX-MS)-which allows the mapping of residue-level changes in a structural conformation upon protein modification or protein/Ligand binding35,50,51,52,53,54,55. HDX-MS uses the continuous exchange of backbone hydrogens by deuterium, the rate of which is affected by the chemical environment, accessibility, and covalent and non-covalent bonds56. HDX-MS tracks these exchange processes using a deuterated solvent, commonly heavy water (D2O), and allows measurement based on the change in molecular weight following the hydrogen to deuterium exchange. Slower rates of hydrogen-deuterium exchange can result from hydrogens participating in hydrogen bonds or, simply, from steric hindrance, which indicates local changes in structure57. Changes upon a ligand binding or post-translational modifications can also lead to differences in the hydrogen environment, with a binding resulting in differences in the hydrogen-deuterium exchange (HDX) rates46,53.
We applied this technology to 1) map Hsp33 regions which rapidly unfold upon oxidation, leading to the activation of Hsp33, and 2) define the potential binding interface of Hsp33 with its full-length misfolded substrate, citrate synthase (CS)38.
The methods described in this manuscript can be applied to study redox-dependent functions of proteins in vitro, defining anti-aggregation activity and the role of structural changes (if any) in protein function. These methodologies can be easily adapted to diverse biological systems and applied in the laboratory.
1. Preparation of Fully Reduced and Fully Oxidized Proteins
2. Light Scattering Aggregation Assay
Note: All concentrations in this assay are chaperone- and substrate-specific, and should be calibrated. All buffers should be 0.22 µm-filtered, as it is extremely important that the buffers are free of any particles or air bubbles and the cuvettes are clean and dust-free. It is very important to use a stirrer placed in the quartz cuvette. Check different stirrer sizes and shapes in order to ensure an efficient mixing of the entire solution without producing undesirable air bubbles. Moreover, there are different flouorospectrometers available in laboratories and facilities. Here, a specific fluorospectrometer (see Table of Materials) was used. Different instruments have a diverse sensitivity, measurement speed, and sampler parameters. Therefore, the exact measurement parameters (e.g., emission and excitation bandwidth, sensitivity, and others) should be optimized using a known aggregation-prone protein and its corresponding conditions. Using citrate synthase (CS) and/or luciferase as initial substrates in nanomolar concentrations is recommended.
3. Hydrogen-deuterium Exchange Mass Spectrometry
The two methods presented make it possible to follow the kinetic activity and dynamics of protein interactions between a chaperone and its substrate. Moreover, the reduction-oxidation protocol allows the preparation of a fully reduced and fully oxidized chaperone, giving a more in-depth understanding of the activation mechanism of redox-dependent disordered chaperones.
First, we used light scattering in order to examine the redox-dependent activity of the chaperone. Light scattering was performed on a chemically and thermally denatured CS protein in the presence of an oxidized (active) or reduced (inactive) chaperone (Figure 1). Chemical denaturation leads to a rapid CS aggregation induced by the refolding of a fully denaturized protein in unfavorable buffer conditions. On the other hand, the thermal-induced aggregation results from a relatively slow unfolding of the natively folded substrate. Therefore, these different types of aggregation processes vary in their kinetic parameters. Moreover, different chaperones can vary in their ability to prevent the aggregation of the same substrate in different aggregation modes.
In both forms of denaturation, the addition of oxidized Hsp33 in a molar ratio of 1:4 (CS: Hsp33) completely abolished aggregation, lowering the 360 nm readings to negligible values. The presence of a reduced Hsp33, on the other hand, had no effect on the CS stability and gave an aggregation curve similar to the one detected in the absence of a chaperone (Figure 1).The results were analyzed and cleaned from background noise using Kfits, as schematically described in Figure 2.
The outline of the HDX-MS technique begins with the incubation of the chaperone with deuterium oxide, followed by quenching and digestion, and finally MS analysis and hydrogen-deuterium exchange profiling (Figure 3). During HDX-MS, the chaperone was incubated on the tray at 25 °C in a D2O-containing buffer. After a specific incubation time controlled by the sample handling robotic system, the protein solution was transferred to the quenching solution, acidic and denaturing, on the tray at 0 °C. The low pH and low temperature slows the hydrogen exchange and preserves the deuteration levels of all amide hydrogens, while the denaturing chemical unfolds the protein, enabling it to be properly digested. The robotic system transfers the sample from the tray at 0 °C to the cooling box where it flows into the online pepsin digestion column. Immediately after the protein digestion, the peptides proceed to the C18-trap column for the desalting and removal of fast exchangeable D2O (mainly located on the side chain atoms) and are then separated using the C18 column and analyzed using mass spectrometry. The sample flow is controlled by a two-valve system, which 1) ensures the separation of the pepsin and C18 column buffers in order to prevent the inactivation of the pepsin by organic solvents, and 2) enables the short desalting of the peptides to remove fast exchangeable D2O molecules and salts (Figure 4).
After the computational analysis, we receive a deuteration profile for each peptide, showing a change in mass as a function of the incubation time in D2O. The HDX Workbench software allows the comparison of experimental replicates in order to create statistical analyses of each condition (e.g., an active chaperone in an unbound form). The next step is a comparison of the deuteration curves between different samples; for example, a bound chaperone and an unbound chaperone. These comparisons of different chaperone states can reveal the structural perturbations that accompany substrate binding. Residues that exhibit a slower exchange in the bound state are likely interacting with a binding partner. It is important to note that decreased hydrogen-deuterium exchange rates can also indicate a refolding of a specific region upon binding without the actual direct interaction with the substrate (Figure 5A). The HDX Workbench software allows the examination of the results in the "perturbation" view by showing the deuteration with a standard error over the coverage of the whole protein.
In this case, HDX-MS was used to compare the deuteration pattern between the bound and unbound chaperone Hsp33 to its substrate CS. The results reveal a client-interaction site within the C-terminal redox switch domain of the chaperone (Figure 5B). While reduced, Hsp33 has a completely ordered structure, where the interaction sites are buried. Hsp33 loses its structure and becomes functional when it senses oxidative stress; hence, we compared the reduced and oxidized Hsp33 under both bound and unbound conditions (Figure 5C). The results show that while the reduced Hsp33, whether bound or unbound, produces similar peptide curves, the oxidized Hsp33 displays a significant difference. The oxidized Hsp33 samples show a 30% deuteration difference between the bound and unbound chaperone, with specific areas of the bound protein indicating an allosteric hindrance. The analysis of additional peptides from the N-terminal and the thermobile linker regions are shown in Supplementary Figure 3.
Figure 1. Aggregation analysis by light scattering. The aggregation of chemically and thermally denatured CS was monitored in the presence of oxidized Hsp33 (red), reduced Hsp33 (blue), or in the absence of chaperone (black). A light scattering at 360 nm was monitored for 1,200 s. (A) During the chemical aggregation, in the absence of a chaperone or in the presence of a reduced Hsp33, the CS aggregated rapidly, reaching a plateau approximately 300 s into the measurement. (B) During the thermal aggregation, the CS aggregated gradually in the absence of a chaperone or in the presence of a reduced Hsp33. In both assays, the presence of oxidized Hsp33 completely abolished aggregation, as was demonstrated by negligible 360-nm readings. Please click here to view a larger version of this figure.
Figure 2. Removal of noise and data analysis using Kfits. This panel shows a schema summarizing the data analysis and noise removal by the Kfits tool, as described in the text and in Rimon et al.45. Please click here to view a larger version of this figure.
Figure 3. Workflow of the HDX-MS methodology. HDX-MS employs deuterated solvents to determine the chemical environment of amide hydrogens, uniformly distributed along the backbone of the protein. The protein of interest is incubated in a deuterating buffer in its native form for specific time periods, then the hydrogen-deuterium exchange is quenched by acidic conditions at a low temperature. The protein is digested by an enzyme stable under acidic conditions, such as pepsin. Afterward, the peptides are desalted and separated in a short time to avoid a back exchange. Finally, the peptides are analyzed by a mass spectrometer and the deuterium uptake is evaluated by an analysis software, for example by the HDX Workbench free software58. Please click here to view a larger version of this figure.
Figure 4. Components of the fully automated HDX-MS system. (A) This schematic diagram of the HDX-MS represents all the parts of the system: the loading pump and the HPLC pump control buffer flow and the sample transfer within the system. The robotic system contains two syringes and trays which are used to prepare the deuterated sample and transfer the proteins to the on-line digestion column via the input valve of the cooling box (LC compartment). Then, the digested peptides are directed to the C18 trap and separation columns, subsequently separated, and directed to the mass spectrometer. (B) This panel shows the actual HDX system setup as it was created in the lab. (C) This panel shows a schematic presentation of the online-digestion and the peptide separation fluidic configuration. The digestion and separation systems have one valve each that can be switched between load and inject modes. The first valve (on the left) is connected to the injection port and is controlled by the loading pump, directing samples into the pepsin column using the acidic buffer without any organic solvent that can damage the pepsin resin. The sample is transferred to the right valve into the trap column to remove residues of deuterium as well as fast exchanged deuterated atoms (mainly of the side chains). After a brief wash of 1 – 2 min in the trap column, the valve changes its mode to load and the sample is washed into the C18 separation column using the HPLC pump with increasing concentrations of acetonitrile. The sample is transferred to the mass spectrometer for a mass analysis. The length of the tubes is marked. Please click here to view a larger version of this figure.
Figure 5. HDX-MS results. (A) The results are presented as a deuteration percentage over time per protein fragment, generated by the HDX Workbench software. Each graph shows a protein sample, either oxidized or reduced, and compares between bound and unbound samples. The peptide fragments shown here are the peptide YVVITITPSEG found in the linker region and the peptide LQVMPAQNAQQDDFD found in the C-terminus. (B) The final results, presented as the deuteration difference between the bound and unbound complexes, show the perturbation per amino acid. (C) A structural model of the Hsp33 chaperone shows the deuteration uptake differences throughout the linker and C-terminal unstable regions. This panel is created using the PyMol software. Please click here to view a larger version of this figure.
Supplementary Figure 1. Interface of the program operating mass spectrometer. The program is used to optimize and define mass spectrometer method parameters used for the HDX experiment. The method parameters (in the left panel) can be saved in the method, such that is recognized by other programs. Please click here to view a larger version of this figure.
Supplementary Figure 2. This figure shows a screenshot of the software which serves as an integration platform of the robotic sampling handing system and the MS-LC system. The software optimizes the running time by the scheduling of the HDX experiment, following the defined incubation time in the deuterated buffer (blue arrows). For example, above is a diagram of 17 runs of two replicative analyses of the Hsp33 variant STIL, incubated in a deuterated buffer for different times, ranging from 0 – 100 min. Please click here to view a larger version of this figure.
Supplementary Figure 3. This figure shows an analysis of the deuterium uptake of several Hsp33 peptides from different Hsp33 variants, named PGBD and REV34. The plots demonstrate changes in the deuterium uptake of the same region in Hsp33 in unbound (red) and bound (blue) states. Peptides from the N-terminal region show no significant difference in the HDX rates, while fragments from the linker region show a significant decrease in the HDX rates upon the interaction with the unfolded substrate, citrate synthase. Please click here to view a larger version of this figure.
In this paper, we provided protocols for the analysis of redox-dependent chaperone activity and the characterization of structural changes upon the binding of a client protein. These are complementary methodologies to define potential chaperone-substrate complexes and analyze potential interaction sites.
Here, we applied these protocols for the characterization of a complex between the redox-regulated chaperone Hsp33 with a well-studied chaperone substrate CS. We presented two different types of protein aggregation analyses, which differ in their kinetic and initial state: during a chemical denaturation, the substrate starts its unfolding process from the denatured form, while during a thermal aggregation, the unfolding is initiated from the native form of the substrate.
Light-scattering measurements are a useful tool to monitor the relative amount of protein aggregation. While we use this method to determine the active state of the chaperone, it can further be used to study general aggregation conditions, to compare the stability of a different protein, or to study destabilizing mutations both in the substrate and chaperone.
Despite its simplicity, the light scattering method might produce noisy data, with several outliers. To overcome this issue, we developed the Kfits software described above. The Kfits software makes it possible to simply and rapidly remove large quantities of noisy data, as well as calculate the kinetic parameters from the light scattering curve. Kfits is not restricted to protein aggregation and can be applied to any type of kinetic measurements.
Thus, the methodologies described here are simple, easy to perform, and not time-consuming. They can be applied to different molecular chaperones, enabling their redox dependence to be examined within a couple days. Moreover, the anti-aggregation activity of other, non-redox dependent chaperones can be evaluated using the described protocols of light scattering and Kfits. It is important to note that different parameters, such as temperature, protein concentration, and measurement time have to be adjusted to each protein system independently.
In order to gain structural information governing a chaperone working cycle, we presented the HDX-MS methodology. In contrast to the light scattering procedure, it is a more complex technology and requires specific instrumentation, including a mass spectrometer and, preferably, a robotic system for the sample preparation. However, this setup can be established, even without the robotic system, in an existing facility. Once it is established, the procedure is relatively simple and allows the analysis of challenging protein complexes which might be unreached by high-resolution methodologies (e.g., X-ray and NMR).
The authors have nothing to disclose.
The authors are thankful to Meytal Radzinski for her helpful discussions and critical reading of the article, and to Patrick Griffin and his lab members for their unlimited assistance while establishing the HDX analysis platform. The authors are grateful to the German-Israel Foundation (I-2332-1149.9/2012), the Binational Science Foundation (2015056), the Marie-Curie integration grant (618806), the Israel Science Foundation (1765/13 and 2629/16), and the Human Frontier Science Program (CDA00064/2014) for their financial support.
Chemicals, Reagents | |||
Acetonitrile HPLC plus | Sigma Aldrich | 34998-2.5L | solvent |
Formic acid Optima LC/MS | Fisher Chemicals | A117-50 | solvent supplement |
Isopropyl alcohol, HPLC grade | Fisher Chemicals | P750717 | solvent |
Methanol | Fisher Chemicals | A456-212 | solvent |
Tris(hydroxymethyl)aminomethane | Sigma Aldrich | 252859 | buffer |
Trifluoroacetic acid | Sigma Aldrich | 76-05-1 | solvent |
Water for HPLC | Sigma Aldrich | 270733-2.5L-M | solvent |
ZnCl2, Zinc Chloride | Merck | B0755416 308 | reagent |
DTT | goldbio | 27565-41-9 | reducing agent |
PD mini trap G-25 columns GE healthcare | GE healthcare | 29-9180-07 | desalting column |
Potassium Phosphate | United states Biochemical Corporation | 20274 | buffer |
Hydrogen peroxide 30% | Merck | K46809910526 | oxidizing agent |
citrate synthase | sigma aldrich | C3260 | substrate |
HEPES acid free | sigma aldrich | 7365-45-9 | buffer |
Gndcl | sigma aldrich | G3272-500G | denaturant |
Deuterium Chloride Solution | sigma aldrich | 543047-10G | buffer |
Deuterium Oxide 99% | sigma aldrich | 151882-100G | solvent |
TCEP | bioworld | 42000058-2 | reducing agent |
150uL Micro-Insert with Mandrel Interior & Polymer Feet, 29*5mm | La-Pha-Pack -Thermo Fischer Scientific | ||
1.5mL Clear Short Thread Vial 9mm Thread, 11.6*32mm | La-Pha-Pack -Thermo Fischer Scientific | ||
quartz cuvette | Hellma 101-QS | ||
Instruments | |||
Jasco FP-8500 Fluorospectrometer | Jasco | ||
Thermomixer Comfort | Eppendorf | 13058/0 | |
Heraeus Megafuge 16R, bench topCentrifuge | Thermo Scientific | ||
pH meter , PB-11 sartorius | Sartorius | 13119/0 | |
AffiPro Immobilized Pepsin column (20mm length, 2.0mm diameter). | AffiPro | ||
Waters Pre-column (ACQUITY UPLC BEH C18 VanGuard 130 Å, 1.7um, 2.1mmx5mm) | Waters | ||
C18 analytical column (ACQUITY UPLC Peptide BEH c18 Column, 130 Å, 1.7um, 2.1mmx50mm) | |||
Vinyl Anaerobic chamber with Airlock door | COY | ||
Q-exactive-orbitrap mass spectrometer | Thermo-Fischer Scientific | ||
PAL system LHX – robotic system for handling HDX samples | PAL system | https://www.palsystem.com/index.php?id=840 | |
Dionex Ultimate 3000, XRS pump | Thermo Scientific | ||
Dionex AXP-MS auxiliary pump | Thermo Scientific | ||
Software, Software Tools, Database search | |||
Kfits: Fit aggregation Data | http://kfits.reichmannlab.com/fitter/ | ||
Thermo Scientific Xcalibur software | https://www.thermofisher.com/order/catalog/product/OPTON-30487 | ||
Q Exactive MS Series Tune Interface (Tune) | https://tools.thermofisher.com/content/sfs/brochures/WS-MS-Q-Exactive-Calibration-Maintenance-iQuan2016-EN.pdf | ||
Chronos software (Axel Semrau) | http://www.axel-semrau.de/en/Software/Software+Solutions/Chronos-p-966.html | ||
Proteome Discoverer V1.4 software | https://www.thermofisher.com/order/catalog/product/OPTON-30795 | ||
HDX workbench software | http://hdx.florida.scripps.edu/hdx_workbench/Home.html |