Analyzing the Hydrophobic Proteome of the Antarctic Archaeon Methanococcoides burtonii Using Differential Solubility Fractionation Dominic W. Burg,† Federico M. Lauro,† Timothy J. Williams,† Mark J. Raftery,‡ Michael Guilhaus,‡ and Ricardo Cavicchioli*,† School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, 2052, NSW, Australia and Bioanalytical Mass Spectrometry Facility, The University of New South Wales, Sydney, 2052, NSW, Australia Received September 3, 2009
Proteomic studies have proven useful for studying the Antarctic archaeon Methanococcoides burtonii; however, little has been learned about the hydrophobic and membrane proteins, despite knowledge of their biological importance. In this study, new methods were developed to analyze and maximize the coverage of the hydrophobic proteome. Central to the analysis was a differential solubility fractionation (DSF) procedure using n-octyl-β-D-glucopyranoside. The study achieved a significant increase (330) in the total number of known expressed proteins. From 612 identified, 185 were predicted to contain transmembrane domains or be associated with the membrane and 190 to be hydrophobic. The DSF procedure increased the efficacy of identifying membrane proteins by up to 169% and was economical, requiring far fewer runs (12% of machine time) to analyze the proteome compared to procedures without DSF. The analysis of peptide spectral counts enabled the assessment of growth temperature specific proteins. This semiquantitative analysis was particularly useful for identifying low abundance proteins unable to be quantified using labeling strategies. The proteogenomic analysis of the newly identified proteins revealed many cellular processes not previously associated with adaptation of the cell. This DSF-based approach is likely to benefit proteomic analyses of hydrophobic proteins for a broad range of biological systems. Keywords: hydrophobic proteome • LC/LC-MS/MS • detergent fractionation • membrane protein • archaea • methanogen • psychrophile • methylotroph • cell envelope • S-layer • transporter
Introduction Methanococcoides burtonii is a methanogen isolated from a marine-derived lake in Antarctica1-3 and has served as a model organism for studying cold adaptation in the Archaea.1 The capacity to probe molecular mechanisms of adaptation has been facilitated by genomic and proteomic analyses,4-10 including recent proteomic analyses based on the use of isobaric tags for quantification (iTRAQ).11,12 These studies (particularly Allen et al.4) and others assessing membrane lipid composition13 and extracellular polymer production14 have highlighted the importance that the membrane and external surface layer (S-layer) play in the growth and survival of M. burtonii. A limitation of proteomics for studying the composition of the membrane and S-layer has been the availability of methods suitable for solubilizing hydrophobic proteins and determining their identity using LC/LC-MS/MS. Establishing methods to * To whom correspondence should be addressed. Rick Cavicchioli. School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, 2052, NSW, Australia. E-mail
[email protected]; Tel. (+61) 2 9385 3516; Fax (+61) 2 9385 2742. † School of Biotechnology and Biomolecular Sciences. ‡ Bioanalytical Mass Spectrometry Facility.
664 Journal of Proteome Research 2010, 9, 664–676 Published on Web 12/08/2009
improve the recovery of hydrophobic proteins should facilitate the identification of integral membrane and membrane associated proteins involved in signal transduction, the energy generating electron transport chain, transport of ions and solutes, and secretion of proteins. An associated benefit should be the recovery and identification of hydrophobic proteins that form the core of protein complexes (e.g., ribosomes). For hydrophobic proteins to be compatible with mass spectrometry and not interfere with instrumentation, proteins need to be converted into a soluble form while also remaining relatively chemically inert. A number of methods have been developed to improve the analysis of hydrophobic proteins, and several have been applied to extremophilic microorganisms, including archaea.15 Detergent16 and nondetergent17 based methods have been applied to hydrophobic proteins, although the methods tend to require the removal of solubilizing agents prior to MS. The incorporation of 2DGE can also be problematic as hydrophobic proteins tend to precipitate during isoelectric focusing and run as streaks on gels.18 Alternative approaches have used affinity labeling with lipid soluble probes,19 a tube digestion method that facilitates the removal of interfering detergents,20 and a method that involves treatment with high pH and CNBr.21 The method developed by 10.1021/pr9007865
2010 American Chemical Society
Hydrophobic Proteome of Methanococcoides burtonii 22
Blonder et al., which utilizes methanol combined with thermal denaturation and in-solvent digestion has proven to be useful,23 superior to detergent based solubilization,24,25 and compatible with LC/LC-MS/MS.25 The inherent difficulties with recovering hydrophobic proteins for proteomics are also accompanied by issues related to overall sample complexity and the relative concentration of individual proteins. Highly abundant proteins (e.g., metabolic proteins) may be up to 7 orders of magnitude more abundant than other proteins (e.g., transcriptional regulatory proteins).26 As MS relies on intensity based ion selection, the presence of peptides from high abundance proteins masks the selection of the low abundance (low intensity) peptides, and hence their detection. Fractionation strategies help to reduce complexity and enable less abundant peptides to be detected. It is particularly important to reduce the high abundance soluble proteins for proteomics of hydrophobic proteins.18 While many off-line and predigestion methods are suitable for use with soluble proteins, the application of prefractionation strategies to hydrophobic proteins is more challenging. Ramos et al.27 utilized a combination of detergents and chaotropic reagents to separate an insoluble fraction based on the principle of differential solubility, and were able to achieve good separation by combining this method with a gel-based desalting step and LC-MS/MS. This study27 appears to be the only one reporting the use of fractionation as a strategy for proteomic analysis of hydrophobic proteins. In the present study, we demonstrate that it is possible to improve the coverage of hydrophobic proteins from M. burtonii through the use of a differential solubility fractionation (DSF) method using increasing concentrations of the powerful nonionic detergent, n-octyl-β-D-glucopyranoside (OGP) followed by detergent removal, in-solvent digestion, and LC/LC-MS/ MS. The approach greatly improved the efficiency and total number of identifications of hydrophobic proteins. By performing a large number of LC/LC-MS/MS runs, we were also able to analyze peptide spectral counts to determine differences in protein abundance between cells grown at 4 and 23 °C. The success of using this DSF approach with M. burtonii, indicates it is likely to be a method that will benefit proteomic analyses of numerous types of biological systems.
Experimental Procedures Culture Conditions. Cultures of M. burtonii (DSM 6242) were grown anaerobically in MFM at 4 or 23 °C, under a gas phase of 80:20 N2/CO2.2,7 The cultures were prepared in 100 mL volumes from a 1:100 inoculation of actively growing cells preconditioned with at least one passage at each growth temperature. Cells were harvested at mid logarithmic phase (OD620 of 0.25) and pellets collected by centrifugation at 3200× g for 35 min at 4 °C, and cell pellets stored at -80 °C. Hydrophobic Protein Extraction. Hydrophobic proteins were extracted from cell pellets using a method modified from Blonder et al.22 Cell pellets were suspended in 1 mL disruption buffer (50 mM Tris-HCl, 2 mM EDTA, pH 7.2) with PMSF added to 2 mM. The cellular material was mixed using a vortex and ultrasonically disrupted using a Branson digital sonifier 250 (Branson Ultrasonics, Danbury, CT) set at 30% amplitude and 0.5 s pulse for 2 min. To remove any media precipitates, lysates were centrifuged at 1500× g for 5 min at 4 °C, and a carbonate extraction performed on the supernatant. The cellular proteins were diluted to 10 mL in ice-cold, 0.1 M NaCO3 pH 11.2 and agitated for 1 h in an ice-water bath. The carbonate-extracted
research articles material was centrifuged at 115 000× g for 90 min at 4 °C, and the supernatant discarded. The insoluble pellets were washed twice with dH2O, resuspended in 5 mL freshly prepared 40 mM ammonium bicarbonate (ambic), and centrifuged at 115 000× g for 30 min, and the supernatant discarded. The insoluble pellet was washed and resuspended in 2 mL 40 mM ambic and sonicated (15% amplitude, 10-20 s). Concentration and buffer exchange was performed in 4 mL Amicon 5 kDa centrifugal concentration units (preconditioned and washed with fresh 40 mM ambic at 5000× g for 30 min at 6 °C) by centrifuging the protein material at 5000× g for 45 min at 6 °C. The protein concentrate was resuspended in 40 mM ambic and centrifuged at 5000× g for 45 min at 6 °C to achieve a final volume of 500-250 µL. Proteins were resuspended by placing the Amicon units in an ultrasonic bath (Edwards Instruments, Thebarton, South Australia) and flushing the membranes of the filter with a pipet. Insoluble protein samples were stored at -80 °C. Differential Solubility Fractionation. The nonionic detergent OGP (Sigma, St Louis, MO) was chosen for its ability to solubilize membrane proteins and ease of removal from samples.28,29 Whole hydrophobic protein extracts were pelleted by centrifugation at 20 000× g for 30 min at 4 °C, and the supernatant discarded. The pellet was washed by resuspending in 1 mL 40 mM ambic and centrifuging at 20 000× g for 30 min at 4 °C, and the supernatant discarded. The pellet was resuspended in 1 mL 0.5 mM OGP, dissolved in 40 mM ambic, vortexed for 5 s, placed in an ultrasonic bath for 20 s, and vortexed for 5 s. The sample was then centrifuged at 20 000× g for 30 min at 4 °C, the supernatant collected and concentrated and desalted using an Amicon concentration unit (see above) using 5 exchanges of buffer. The procedure was repeated using incremental increases in detergent concentration (0.5, 1.25, 2.5, 5, 12.5, 20, 30, 100, 500 mM) applied to the protein pellet, and after buffer exchange, protein fractions were stored at -80 °C. Preparation of Hydrophobic Proteins for Mass Spectrometry. Hydrophobic protein extracts, including those from DSF, were treated using a method modified from Blonder et al.22 Samples containing 50 µg of protein (concentration determined by the Bradford microassay method30) were diluted to 90 µL with 40 mM ambic, reduced with 5 µL 0.1 M DTT (final concentration 5 mM) at 60 °C in the dark for 45 min, and alkylated with 5 µL 0.3 M IDA (final concentration 15 mM) at 60 °C for 45 min in the dark. The reduced and alkylated proteins were thermally denatured at 90 °C for 1-2 min and solubilized with 150 µL HPLC grade methanol (final methanol concentration 60%). Alternative solvents were also trialed. The proteinsolvent mixture was cooled and further solubilized in an ultrasonicator bath. If insoluble material visibly remained, samples were sonicated for 5-10 s at 15% amplitude. Solubilized proteins were digested with sequencing grade porcine modified trypsin (Promega, Madison, WI) at a trypsin to protein ratio of 1:20 (µg) at 37 °C for 5 h, the solution vacuum-dried and the sample stored at -80 °C. Sample Cleanup. Sample cleanup was performed using offline chromatography with a C18 reverse phase (RP) cartridge, with some samples (e.g., from DSF) requiring prior treatment with strong cation exchange (SCX) (Applied Biosystems cation exchange system with an Opti-Lynx cartridge holder). SCX was performed at a flow rate of 9.5 mL h-1 using a 1 mL glass needle (Alltech, Baulkham Hills, NSW) and a syringe pump (KD Scientific, Holliston, MA). Vacuum-dried sample pellets (see Preparation of Hydrophobic Proteins for Mass Spectrometry) were resuspended in 5 mL of loading buffer (10 mM KH2PO4 Journal of Proteome Research • Vol. 9, No. 2, 2010 665
research articles in 25% ACN pH 3.0), centrifuged at 5000× g for 5 min at 4 °C, and the supernatant retained. The sample was adjusted to pH 2.5-3.3 using glacial acetic acid. The sample was loaded onto the SCX column (prepared by washing with 2 mL of load buffer) and washed with 1 mL of load buffer. Peptides were eluted with 0.5 mL of elution buffer (10 mM KH2PO4, 350 mM KCl in 25% ACN pH 3.0) and the eluted samples vacuum-dried. Dried samples were immediately stored at -80 °C, or subjected to RP chromatography (flow rate, 9.5 mL h-1). Vacuum-dried samples were resuspended in 500 µL 0.2 M heptafluorobutyric acid (HFBA) (Pierce Biotechnology, Rockford, IL) and mixed by vortexing. An RP macrotrap (Microm Bioresources, Auburn, CA) was fitted into a steel column holder and was washed with 0.5 mL ACN, followed by 0.5 mL 50% 0.2 M HFBA: 50% ACN. An equilibration step was carried out by injecting 1.5 mL 0.2 M HFBA. The sample was then injected, and the column containing bound peptides washed with 1.5 mL 0.2 M HFBA. The sample was eluted by injecting 250 µL 50% 0.2 M HFBA: 50% ACN, followed by 250 µL ACN. The column was then washed in 1 mL ACN and stored at room temperature for further use. The eluted sample was vacuum-dried and stored at -80 °C until needed. Mass Spectrometry. Dried peptide pellets were dissolved in 50 µL 0.05% HFBA/1% formic acid, and a 1:20 dilution of sample:HFBA/formic acid solution. Prior to all sample runs the instruments were calibrated by running 1 µL of 50 fmol µL-1 glufibrinopeptide standard (Sigma, St Louis, MO). Peptides from samples were separated by nano-LC using a Cap-LC autosampler system (Waters, Milford, MA).31 Ten microliters was loaded onto a SCX micro column (0.76× ∼15 mm) containing Poros S10 or S20 resin (Applied Biosystems, Foster City, CA). Peptides were eluted sequentially using 5, 10, 15, 20, 25, 30, 40, 50, 100, 250, 500, and 1000 mM ammonium acetate (20 µL). The unbound load fraction and each salt step were concentrated and desalted onto a micro C18 precolumn (500 µm × 2 mm, Michrom Bioresources, Auburn, CA) with buffer A (H2O:CH3CN,98:2; 0.1% formic acid) at 15 µL min-1. After a 10 min wash the precolumn was switched into line with a fritless analytical column (75 µm × ∼10 cm) containing C18 reverse phase packing material (Magic, 5 µ, 200 Å, Michrom Bioresources, Auburn, CA) as described by Gatlin et al.32 Peptides were eluted using a linear gradient of buffer A to 45% buffer B (H2O/CH3CN, 80:20; 0.1% formic acid) at ∼300 nL min-1 over 90 min. The precolumn was connected via a fused silica capillary (10 cm, 25 µm) to a low volume tee (Upchurch Scientific, Oak Harbor, WA, USA) and high voltage (2400 V) applied, and the column tip positioned ∼0.5 cm from the Z-spray inlet of an Ultima API hybrid QTof tandem mass spectrometer (Micromass, Manchester, England). Positive ions were generated by ESI and the QTof operated in data dependent acquisition mode. A TOF MS survey scan was acquired (m/z 350-1700, 1 s) and the 3 largest multiply charged ions (counts >20) were sequentially selected by the quadrupole for MS/MS analysis. Argon was used as collision gas and an optimum collision energy chosen (based on charge state and mass). Tandem mass spectra were accumulated for up to 3 s for each precursor (m/z 50-2000). Peak lists were generated by MassLynx (Micromass, Manchester, England), using the Mass Measure program. Data Processing. Data generated by the mass spectrometers were processed to a format suitable for Mascot (Matrix science London, UK; version 2.1 or 2.2) by MassLynx. Sequential salt elutions from LC/LC-MS/MS experiments were combined into 666
Journal of Proteome Research • Vol. 9, No. 2, 2010
Burg et al. a single file using Mergefile (Matrix Science, London, England), and searched using Mascot against an in silico digestion of the local M. burtonii protein FASTA database (2431 sequences, 729 161 residues) created in Mascot using the following parameters: tryptic digestion; variable modifications of carbamidomethylation and oxidation of methionine; a peptide mass tolerance of ( 0.25 Da; a fragment mass tolerance of (0.2 Da; maximum number of missed cleavages set to 1; peptide rank of 1. A decoy database, created using Mascot by randomizing the M. burtonii local FASTA database, was searched using the same parameters. All spectra which matched the databases with a Mowse score of 30 were manually inspected to ensure ion progressions of 4 or more consecutive ions of a single class (e.g., 4 consecutive y-type ions). Any matches that did not meet these criteria were rejected. Two peptides were required for protein identification. From the identifications in both the M. burtonii database and the decoy database it was possible to calculate the false discovery rate (FDR) for any given experimental run.33 Any experiment that had a FDR >0.02 or (2%) was rejected. Identifications were then moved to a database for further processing. Data from experiments also underwent secondary searching using the program Scaffold 2 (version Scaffold_2_00_06, Proteome Software Inc., Portland, OR). The Scaffold searches were used to identify differences in identification between fractions and also, using normalized peptide spectral data, were used to identify trends within the data set. All MS/MS samples were analyzed using Mascot and X! Tandem (www.thegpm.org; version 2007.01.01.1). Both programs were set up to search the M. burtonii database assuming digestion with trypsin. X! Tandem was searched with a fragment ion mass tolerance of 0.10 Da and a parent ion tolerance of 0.25 Da. Mascot was searched with a fragment ion mass tolerance of 0.20 Da and a parent ion tolerance of 0.25 Da. Oxidation of methionine and iodoacetamide derivative of cysteine were specified in the programs as variable modifications. Scaffold was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 95.0% probability as specified by the Peptide Prophet algorithm.34 Protein identifications were accepted if they could be established at greater than 95.0% probability and contained at least 1 identified peptide for each condition for the purpose of trend identification. Protein probabilities were assigned by the Protein Prophet algorithm.35 Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. To determine differences between categories (4 and 23 °C), t tests were performed within the Scaffold software package, and statistical differences accepted at p 0.05) were found between the solvents tested for cells grown at either 4 or 23 °C, and based on its use in other studies,22,23 methanol was adopted as the solvent for all protein extractions. Differential Solubility Fractionation. Washed insoluble extracts were treated with incrementally increasing concentrations of the nonionic detergent OGP, and the proteins subjected to buffer exchange and concentration prior to in-solvent digestion and LC/LC-MS/MS. The separation procedure produced 4-6 fractions containing useful quantities of protein. Appreciable recovery occurred with concentrations of OGP as low as 0.5 mM, and all proteins were solubilized after treatment with 20 mM OGP (i.e., protein was not detected in remaining residue) (Figure 1).
Figure 1. Comparison of protein types during incremental steps of DSF. As the total number of identifications in any LC/LC-MS/ MS experiment varies, in order to compare the distribution of proteins between runs data is presented as the percentage of total identifications. Data is from one representative experiment performed on biomass from cells grown at 4 °C, and similar patterns were seen in all repeat experiments. Table 1. Comparison of the Frequency of HPP Protein Types Identified from DSF and Non-DSF Treatments HPP type
average
rangea
Membrane - no DSF Membrane - DSF Hydrophobic - no DSF Hydrophobic - DSF NIW - no DSF NIW - DSF
27% 38% 26% 38% 31% 40%
16-38% 27-63% 23-40% 26-45% 25-48% 31-56%
a Lower and upper proportion of proteins identified in the specified class for proteins identified after no DSF treatment (31 experiments) or DSF treatment (25 experiments).
The proportion of membrane, hydrophobic and NIW proteins generally increased with increasing concentrations of OGP (Figure 1), with significant differences in abundance between the fractions with lowest (0.5 mM) and highest (20 mM) concentrations of detergent (ANOVA p
