Here we present a protocol to perform polysome profiling on the isolated perfused mouse heart. We describe methods for heart perfusion, polysome profiling, and analysis of the polysome fractions with respect to mRNAs, miRNAs, and the polysome proteome.
Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ischemia and reperfusion using the isolated perfused mouse heart coupled with polysome profiling. To further understand the dynamic changes in protein translation, we characterized the mRNAs that were loaded with cytosolic ribosomes (polyribosomes or polysomes) and also recovered mitochondrial polysomes and compared mRNA and protein distribution in the high-efficiency fractions (numerous ribosomes attached to mRNA), low-efficiency (fewer ribosomes attached) which also included mitochondrial polysomes, and the non-translating fractions. miRNAs can also associate with mRNAs that are being translated, thereby reducing the efficiency of translation, we examined the distribution of miRNAs across the fractions. The distribution of mRNAs, miRNAs, and proteins was examined under basal perfused conditions, at the end of 30 min of global no-flow ischemia, and after 30 min of reperfusion. Here we present the methods used to accomplish this analysis—in particular, the approach to optimization of protein extraction from the sucrose gradient, as this has not been described before—and provide some representative results.
The heart responds to the injury of ischemia (I) and reperfusion (R) in a dynamic fashion. However, there is little insight into acute changes in protein synthesis during the response. To address this, we took advantage of the well-established method of polysome profiling1 to identify changes in protein abundance that reflect redistribution of ribosomes and translational regulatory factors from cytosol to polysomes, and the increase in newly synthesized proteins (NSPs). In the setting of I/R, the increase in new protein synthesis occurs in a time frame that is inconsistent with transcription of new mRNAs2; moreover, discordance between mRNA expression levels and protein abundance has been reported3. For these reasons, we chose to analyze the changes in the dynamic proteome as reflected by protein translation. To do this, we quantify mRNA in the polysome fractions, and analyze the protein composition in the polysome fractions. Finally, because microRNAs (miRs) regulate availability of mRNAs for translation and can interfere with efficiency of protein translation4,5, we examined the distribution of miRs in the polysome fractions, focusing on the response to I/R.
We chose to use the isolated mouse Langendorff perfusion model and harvested tissue under basal conditions of continuous perfusion, after 30 min global no-flow ischemia, and after 30 min of ischemia followed by 30 min of reperfusion. We then solubilized the heart tissue and separated polysomes over a sucrose gradient, followed by proteomic analysis and selective detection of mRNAs and miRNAs by PCR and microarray, respectively. This combination of methods represents a powerful approach to understanding the dynamic proteome, enabling simultaneous detection of mRNA, miRNA, and NSPs, as well as the redistribution of regulatory proteins, miRNA, and mRNA between nontranslating fractions, low-efficiency polysomes, and high-efficiency polysomes (see Figure 1). Insights into the dynamic regulation of this process will be extended by further analysis of phosphorylation of key regulatory factors such as eIF2α or mTOR. These individual steps are now described in detail.
All animal studies were performed in accordance with institutional guidelines and approved by the Institutional Animal Care and Use Committee of Cedars-Sinai Medical Center.
1. Langendorff Perfusion of Mouse Heart
2. Tissue Homogenization, Solubilization, and Sucrose Density Gradient Sedimentation
3. Isolation and Analysis of mRNAs from Polysome and Nontranslating Fractions
4. Isolation and Analysis of miRNAs from Polysome Fractions and Nontranslating Fractions
5. Proteomic Analysis
mRNA analysis
mRNA results can be expressed as a distribution of a particular mRNA in each fraction (Figure 3A); for quantification, combine polyribosomal translating fractions and compare to the non-translating fraction (Figure 3B), presenting a ratio of mRNA abundance in translating to nontranslating fractions. Additional information is gained by examining the high efficiency polysome fractions separately from low-efficiency polysome fractions (and separate from nontranslating fractions). This is particularly important when analyzing miRNAs, which are enriched in the low-efficiency fractions (where they interfere with protein translation of their target mRNAs).
Representative results for a particular mRNA that changes its distribution across the translating and nontranslating fractions after the mouse hearts were subjected to ischemia and ischemia/reperfusion compared to sham are shown in Figure 4.
miRNA array analysis
Representative results from a miRNA array analysis are shown in Figure 5. Here, a subset of miRNAs (custom-designed array plate) were analyzed in the pooled heavy fractions indicating that 22 miRNAs were associated with polysomes during ischemia, 9 miRNas during ischemia and reperfusion, with 7 that were common to both conditions. This shows that the association of miRNAs is dynamic in response to the stresses of ischemia and reperfusion.
Proteomic analysis
Analysis of heavy, light and non-translating fractions of sham (control) sample:
881 of total proteins were identified by mass spectrometry; 3, 46 and 208 proteins of total were unique to heavy, light and non-trans fractions, respectively (Figure 6A). The majority (88%) of mitochondrial ribosomal proteins (28S and 39S) were identified in light fraction (36 out of 41) and a majority (88%) of cytosolic ribosomal proteins (40S and 60S) were identified commonly in both heavy and light fractions (53 out of 60) confirming efficient separation and proteomic ability to identified heavier cytosolic vs lighter mitochondrial ribosomal proteins. The subset of identified mitochondrial and cytosolic ribosomal proteins is shown in Figure 6B.
Figure 1: Typical UV absorbance profile of polysome fractions on sucrose gradient. The first three fractions represent void volume in the tubing. The high efficiency (high molecular weight, HMW) fractions are collected in fractions 4-7, the low efficiency (low molecular weight, LMW) fractions in 8-11, and the non-translating (and remaining cytosolic material) is collected in fractions 12-15 (nontranslating, NTR). The red line indicates conductivity, and the blue trace indicates UV absorbance at 254 nm. On the right is a cartoon of a test tube with sucrose gradient, showing distribution of polysomes after sedimentation. Please click here to view a larger version of this figure.
Figure 2: RNA integrity control analysis on Bioanalyzer. RNA integrity number (RIN) of total RNA isolated from heart whole lysate. RIN is calculated according to 18S and 28S peaks. RIN range: 1-10, and RIN = 10 represents a very good integrity. Please click here to view a larger version of this figure.
Figure 3: Representative profile of mRNA distribution in sucrose gradient. Hearts were subjected to basal Langendorff perfusion or ischemia and reperfusion (I/R). (A) Heart lysates were resolved on sucrose gradient and mRNA content for GAPDH (left) and COX4 (right) were determined in each fraction. Plot shows relative mRNA abundance in each fraction (fraction number on x-axis) for basal perfusion (sham, red line and diamonds) and ischemia/reperfusion (I/R, blue line and squares). Superimposed on the plot are UV absorbance indicating total mRNA content (light gray curve) and conductance (straight gray sloping line). Boxes indicate how fractions were pooled. (B) Bar graph plot shows ratio of mRNA abundance in translating (polysomes) vs nontranslating (NT) fractions for GAPDH (left) and COX4 (right) mRNAs. Please click here to view a larger version of this figure.
Figure 4: Representative mRNA results. Quantitation of one mRNA in the pooled fractions (HMW, LMW, NTR) showing changes according to the experimental group. Polysome fractionation of mouse hearts was performed after Langendorff perfusion. Results are plotted as % of total mRNA (upper panel) and as ratio of polysomes (HMW+LMW) to nontranslating fraction (NTR). Error bars represent results from 5 hearts per group (sham, ischemia, or I/R). Please click here to view a larger version of this figure.
Figure 5: Representative miRNA results. Venn Diagram of a pathway focused miRNA analysis showing up and downregulated miRNAs in heavy fraction pools of mice samples after heart ischemia or ischemia and reperfusion. Cut-off value: 1.5 fold. Please click here to view a larger version of this figure.
Figure 6: Proteins identified by mass spectrometry. (A) Venn diagram of the proteins common and unique to heavy, light and non-trans fractions. (B) Subset of mitochondrial and cytosolic ribosomal proteins identified. Please click here to view a larger version of this figure.
Figure 7: Schematic workflows for protein extraction methods tested. The protein extraction methods were tested by using sham (control) sample and heavy (high efficiency polysomes) fraction with highest sucrose content. Numbers in red indicate the number of proteins that were identified by mass spectrometry; where two numbers are shown, they are from two separate experiments. The detailed description is given in the text. Please click here to view a larger version of this figure.
FRACTIONS | GENE Ct | LUCIFERASE Ct | ΔCt | 2ΔCt | SUM OF ALL FRACTIONS | % OF EACH FRACTION | Polysome/NTR Ratio |
High efficiency (HMW) | 28.75 | 22.79 | 5.96 | 0.016 | 0.046 | 34.64 | 2.77 |
Low efficiency (LMW) | 28.43 | 22.63 | 5.80 | 0.018 | 38.81 | ||
Non Translating (NTR) | 29.12 | 22.77 | 6.35 | 0.012 | 26.55 | ||
Polysome/NTR Ratio = (HMW + LMW)/NTR |
Table 1: Sample analysis of mRNA. Method of analysis of one mRNA is shown for the different pooled fractions (HMW, LMW, NTR) after quantitative PCR. ΔCt = gene Ct – luciferase Ct, and the 2ΔCt is 2ΔCt.
Find the SCM minimum value: 22.77 | |||
Sample 1 | Sample 2 | Sample 3 | |
Ct MOI | 22.92 | 22.36 | 22.58 |
Ct SCM | 22.81 | 22.77 | 22.9 |
Ct REF | 23.27 | 23.55 | 23.19 |
Normalize all the SCM values to this minimum | |||
Sample 1 | Sample 2 | Sample 3 | |
Ct SCM | 0.05 | 0 | 0.13 |
Subtract these values from the Ct values of MOI and REF | |||
Sample 1 | Sample 2 | Sample 3 | |
Ct MOI | 22.87 | 22.36 | 22.45 |
Ct REF | 23.22 | 23.55 | 23.06 |
Table 2: Sample real-time PCR calculation for miRNA expression comparison in polysome and nontranslating fractions. miRNAs of interest (MOI) and reference gene (REF) were analyzed in the pooled heavy fractions of mice after ischemia or ischemia/reperfusion. The Ct values were first normalized to the spike-in control (SCM) Ct value, then the 2-ΔCt formula was used to compare miRNA expression.
Method | Sample volume [mL] | # of proteins identified | コメント |
FASP | 1 | 227 | bulk of sucrose precipitated on filter |
acetone precipitation | 0.6 | 372 | viscous sludge of sucrose at the tube bottom; 4:1 (reagent:sample) volumes; no visible protein pellet |
chloroform/methanol precipitation | 0.32 | 389 | viscous sludge of sucrose at the tube bottom; 8:1 (reagent:sample) volumes; no visible protein pellet |
TCA precipitation (at 4 °C) | 0.5 | 405, 415 | no sucrose precipitation; 0.12:1 (reagent:sample) volumes; visible pellet at the tube bottom |
re-precipitation | 85, 60 | additional TCA precipitation of supernatant after first pellet was collected | |
TCA precipitation (at -20 °C) | 0.5 | 440, 430 | no sucrose precipitation; 0.12:1 (reagent:sample) volumes; visible pellet at the tube bottom |
re-precipitation | 81, 55 | additional TCA precipitation of supernatant after first pellet was collected |
Table 3: Comparison of protein extraction methods. FASP, acetone precipitation, chloroform/methanol precipitation, and TCA precipitation at 4 °C and -20 °C were evaluated. The goal was to maximize the number of proteins identified. TCA precipitations were evaluated on a second batch of material to confirm reproducibility.
Polysome profile analysis allows for the study of protein translation by analyzing the translational state of a specific mRNA or the whole transcriptome6,7. It is also of great help when local translation needs to be studied such as synaptosomes8. Traditionally, this method involves the separation of mono- and polyribosomes and the associated mRNAs on a sucrose gradient which could be coupled with genomic or proteomic techniques to obtain the intended results6,9. For instance, a recent study performed by our group has revealed a post-transcriptional regulatory mechanism executed in the heart of patients undergoing CPB, which mimics ischemia/reperfusion injury. Taking advantage of polysome profile analysis, we have shown an increase in translation of nuclear-encoded mitochondrial proteins in heart after CPB procedure2.
The dynamic proteome polyribosomal profiling approach presented here can reveal changes in the population of mRNAs associated with polyribosomes and the proteins that are being actively translated. As translation of mRNAs is governed in part by miRNAs, analysis of miRNAs in these fractions can reveal additional insights. In fact, several studies have modified this method and proved it to be a suitable and reliable approach to investigate the miRNA mode of regulation10,11.
Many studies have been conducted in the last decade delving into the role of miRNAs, considering their importance in various biological functions12,13. Since miRNAs act through base-pairing with counterpart mRNAs so as to mark them for degradation, polysome profile analysis has been performed and shown that miRNAs are in fact found in the polysome fractions, targeting translating mRNAs14,15,16. miR-21 is a good example where it is associated with a low repression and weak polysomes binding in normal cells, while in cancer cells, the association with polysomes is increased and the repressive effect is much stronger17.
In this study, Real-time PCR analysis was done using the Ct values of the miRNAs of interest (MOI), the Ct values of the spike-in control miRNA (SCM) to reduce technical variations and the Ct value of a reference gene or miRNA (REF) which is stable among samples. The first step was to normalize the Ct values of the MOI and the REF to the Ct values of the SCM. Then there was a second step normalization of the MOI to the REF and the resulting value was used to calculate the 2-ΔCt formula. These values or fold-change values can be used to demonstrate differences between groups.
Since the extraction of proteins is difficult from polysome fractions, most of the studies performed until now, have used the fractions directly for western blot analysis. They simply sediment the protein content of each fraction and mix it with SDS-loading buffer to use for SDS-PAGE analysis8,18. Here, we have developed a method which allows us to not only extract mRNAs and miRNAs after fractionation, but also to obtain peptides and proteins with a high quality to proceed with Mass Spectrometry analysis.
This approach could be extended further by actively measuring the newly synthesized proteins using metabolic labeling such as biorthogonal amino acid homolog, such as azidohomoalanine (AHA) for methionine19,20. AHA incorporation followed by click chemistry allows for incorporation of a biotin tag followed by streptavidin purification of all proteins that incorporated AHA. This allows definitive identification of newly synthesized proteins — the other part of the dynamic proteome. Detection of miRNAs that redistribute among the translating and nontranslating fractions in response to a stimulus (here with I/R) allows interrogation of the dynamic regulation of protein translation. However, the factors that recruit miRNAs to the vicinity of ribosome-bound mRNA remain to be identified and systematically investigated.
In our study, in addition to TCA precipitation, we tested three other methods for protein extraction from polysome fractions: i) FASP (filter-aided sample preparation)21, ii) acetone precipitation, and iii) chloroform/methanol precipitation. The suitability of the methods was evaluated based on both the ability to process fractions with high concentration of sucrose (up to 50%) and number of proteins identified by mass spectrometry (Figure 7 and Table 3).
For FASP method, we followed the protocol of sample preparation given by a FASP Protein Digestion Kit that employed an ultrafiltration unit with a relative molecular mass cut-off of 30 kDa. This filter unit served as a tool for detergent removal, buffer exchange, protein digestion and peptide elution with the ability to retain high-molecular-weight substances (proteins and DNA) that would otherwise interfere with subsequent peptide separation21. Briefly, the sample was mixed with urea-containing buffer and loaded on unit spin filter with spinning steps as iodoacetamide solution, trypsin solution and sodium chloride solution (elution) were subsequently added. Final filtrate that contained digested peptides was acidified by TFA, desalted and stored for mass spectrometry analysis. Using this method, however, the bulk of precipitated sucrose steadily accumulated on the top of the filter, rendering the centrifugation and washing steps difficult.
For acetone precipitation and chloroform/methanol precipitation, multiple volumes of solvents were needed to precipitate proteins from a single volume of sample. This limited the size of sample volume applied when the precipitation was performed in 1.5 mL tubes (protein low-retention tubes). As well, the viscous sludge of sucrose accumulated at the bottom of tubes after precipitation for both methods and there were no visible pellets at the tube bottom and at the liquid interface after acetone precipitation and chloroform/methanol precipitation, respectively.
Table 3 and Figure 7 show the comparison of four protein extraction methods we used to optimize our experimental workflow. The red numbers given at each method (Figure 7) represent the number of proteins that were identified by mass spectrometry (see Section 5.2 and 5.3). Although sample volumes used for each method were different, chloroform/methanol and TCA precipitations resulted in highest number of proteins identified. However, due to disadvantages mentioned above (sample volume limitation and sucrose precipitation), we opted for TCA precipitation for subsequent experiments.
To find the optimum conditions for the sample processing, TCA precipitation was carried out at various temperatures and TCA concentrations22,23,24. Thus, we performed a precipitation with 10.7% TCA at 4 °C and -20 °C and further precipitated the supernatants with additional 60 µL of TCA (final 19.4% TCA) after pellets were collected. This resulted in four pellets that were analyzed separated by mass spectrometry. In addition, we repeated the whole protocol twice to ensure that obtained results were reproducible. The workflow and the number of proteins identified in the pellets at both 4 °C and -20 °C conditions with two repeated experiments are shown in Figure 7 (numbers in red). Although the analysis of the pellets derived from the supernatants yielded an additional number of proteins (85 and 60 at 4 °C; 81 and 55 at -20 °C); a majority of the proteins were already identified in first pellets and thus, we opted to use 10.7% TCA for all subsequent experiments. Although chloroform/methanol precipitation resulted in a similar number of proteins identified compared to TCA precipitation, we preferred TCA precipitation due to several advantages: i) small volume of solvent needed to precipitate the proteins (60 µL of TCA vs 1.28 mL of chloroform/methanol/water) enabling the use of larger sample volumes if needed while conveniently using 1.5 mL tubes for precipitation, ii) visibility of the pellet at the tube bottom, and iii) no accumulation of sucrose during precipitation steps.
Despite offering in-depth functional information regarding the translational state, a major drawback of this method is the need for fresh and large starting material. Many studies have tried to optimize the conditions using small volume of cells or tissues or add steps to increase the efficiency of extracting RNA and proteins25. Still, tissues obtained from different animals under the same experimental conditions could be pulled together, if need be.
In conclusion, this protocol allows for simultaneous analysis of mRNA, miRNA, and protein from fractions obtained from polysome profiling to study the regulatory mechanisms involved in ischemia/reperfusion. However, further studies are required to see whether the translating mRNAs are induced after ischemia or reperfusion and if they will be turned off upon the removal of stress.
The authors have nothing to disclose.
NIH P01 HL112730 (RAG, JVE), NIH R01 HL132075 (RAG, JVE), Barbra Streisand Women's Heart Center (RAG, JVE), Dorothy and E. Phillip Lyon Chair in Molecular Cardiology (RAG), Erika Glazer Endowed Chair in Woman's Heart Health (JVE) and Czech Academy of Sciences Institutional Support RVO: 68081715 (MS).
Pentobarbital | Vortech Phamaceuticals | 9373 | for euthansia |
Heparin | Sagent | 103424 | used in langendorff preparation |
forceps | Fine Science Tools | 91110-10 | used to hang the heart |
Langendorff system | Radnoti + home made | n/a | A 'four heart' system consisting of custom blown glass, tubing and water baths |
NaCl | Sigma | S7653-5KG | Krebs buffer and Sucrose gradient |
KCl | Sigma | P5405 | Krebs buffer and Lysis buffer |
KH2PO4 | Sigma | P-5504 | Krebs buffer |
MgSO4 | Sigma | M7774-500G | Krebs buffer |
Glucose | Sigma | G5767 | Krebs buffer |
CaCl2 | Sigma | C1016-500G | Krebs buffer |
Sucrose powder | Sigma | S0389-1KG | Sucrose gradient |
MgCl2 | Sigma | 208337 | Sucrose gradient and Lysis buffer |
Tris-base | Sigma | T1503-1KG | Sucrose gradient and Lysis buffer |
Xylene Cyanole | Sigma | X-4126 | Sucrose gradient |
Cycloheximide | Sigma-aldrich | 239763 | Sucrose gradient and Lysis buffer |
RNaseOUT | Life Technologies | C00019 | RNAse inhibitor for Lysis buffer |
Igepal CA-360 (NP40) | Sigma | I3021 | Lysis buffer |
Protease Inhibitor Cocktail tablets, EDTA free | Roche | 5056489001 | |
Tube, Thinwall, Ultra-Clear, 13.2 mL, 14 x 89 mm | Beckman Coulter | 344059 | |
Ultracentrifuge | Beckman | LE-80K | Ultracentrifugation of the gradients |
Rotor | Beckman | SW41 | Ultracentrifugation of the gradients |
Biologic LP (pump) | Biorad | 731-8300 | Fractionation of the gradients |
BioFrac | Biorad | 741-0002 | Fractionation of the gradients |
Eppendorf RNA/DNA LoBind microcentrifuge tubes, 2 mL tube | Sigma | Z666513-100EA | Gradient fraction and RNA extraction |
TRIzol Reagent | Life technologies | AM9738 | RNA extraction |
Luciferase Control RNA | Promega | L4561 | RNA extraction |
Chloroform | Fisher Scientific | C606-4 | RNA extraction |
Glycogen, RNA grade | Thermo Fisher Scientific | R0551 | RNA extraction |
Isopropanol | Sigma | I9516 | RNA extraction |
Ethanol | Sigma | E7023-1L | RNA extraction |
iScript cDNA Synthesis Kit | BioRad | 170-8891 | Reverse transcription |
iTaq Universal SYBR Green Supermix | BioRad | 175-5122 | Quantative PCR |
miRNeasy Micro Kit (50) | Qiagen | 217084 | Kit for total RNA isolation |
miScript II RT Kit (50) | Qiagen | 218161 | Kit for miRNA reverse transcription |
miScript Sybr Green PCR Kit (200) | Qiagen | 218073 | Kit for real-time PCR expression analysis of miRNAs |
Centrifuge 5424R | Eppendorf | For centrifugation of 1.5ml or 2.0ml tubes at different temperatures. Max speed – 21130g | |
Centrifuge 5810R | Eppendorf | For real-time PCR plate centrifugation at different temperatures. Max speed – 2039g | |
My Cycler Thermal Cycler | Bio-Rad | For reverse transcription | |
CFX96 Real-Time System/C1000 Touch Thermal Cycler | Bio-Rad | For real-time PCR analysis | |
miRNeasy Serum/Plasma Spike-in Control | Qiagen | 219610 | For quality control of RNA isolation |
Hard-Shell 96-Well PCR Plates, low profile, thin wall, skirted, green/clear | Bio-Rad | HSP9641 | For real-time PCR analysis |
Microseal 'B' PCR Plate Sealing Film, adhesive, optical | Bio-Rad | MSB1001 | For real-time PCR plate sealing |
Research plus Single-Channel Pipette, Gray; 0.5-10 µL | Eppendorf | UX-24505-02 | For pipetting |
PIPETMAN Classic Pipets, P20 | Gilson | F123600G | For pipetting |
PIPETMAN Classic Pipets, P200 | Gilson | F144565 | For pipetting |
Rainin L-1000XLS Pipet-Lite XLS LTS Pipette 100-1000 µL | Gilson | 17011782 | For pipetting |
Glycogen, RNA grade | Thermo Fisher Scientific | R0551 | Improves total RNA isolation efficiency |
Posi-Click 1.7 mL Tubes, natural color | Denville | C2170 | RNA isolation and storage; reagent mix |
Thermal Cycling Tubes -0.2 mL Individual Caps, Standard 0.2 mL tubes with optically | Denville | C18098-4 (1000910) | Reverse transcription reaction |
Sharp 10 Precision barrier Tips | Denville | P1096-FR | For pipetting |
Sharp 20 Precision barrier Tips | Denville | P1121 | For pipetting |
Sharp 200 Precision barrier Tips | Denville | P1122 | For pipetting |
Tips LTS 1 mL Filter | Rainin | RT-L1000F | For pipetting |
miScript Primer Assay (200) | Qiagen | (it changes according to the miRNA) | For real-time PCR analysis |
Gradient Master ver 5.3 Model 108 | BioComp Instruments | For preparation of sucrose gradients | |
trichloroacetic acid | Sigma Aldrich | T6399 | |
acetone | Sigma Aldrich | 650501 | |
Tris hydrochloride | Amresco | M108 | |
dithiothreitol | Fisher Scientific | BP172 | |
iodoacetamide | Gbiosciences | RC-150 | |
sequencing grade modified trypsine, porcine | Promega | V5111 | |
ammonium bicarbonate | BDH | BDH9206 | |
formic acid, Optima LC/MS | Fisher Chemical | A117 | |
methanol, Optima LC/MS | Fisher Chemical | A454 | |
acetonitrile, Optima LC/MS | Fisher Chemical | A996 | |
Protein LoBind tubes 0.5 mL | Eppendorf AG | 22431064 | |
Protein LoBind tubes 1.5 mL | Eppendorf AG | 22431081 | |
HLB µElution plate 30 µm | Oasis | 186001828BA | |
SpeedVac concentrator | Thermo Scientific | Savant SPD2010 | |
sonicator | Qsonica | Oasis180 | |
centrifuge | Thermo Scientific | Sorvall Legend micro 21R | |
LC trap column PepMap 100 C18 | Thermo Scientific | 160454 | |
LC separation column PepMap RSLC C18 | Thermo Scientific | 164536 | |
mass spectrometer | Thermo Scientific | Orbitrap Elite ion trap mass spectrometer | |
MSConvert software | ProteoWizard Toolkit | ||
Sorcerer-SEQUEST software | Sage-N Research, Inc. |