Prefractionation of Intact Proteins by Reversed-Phase and Anion

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Prefractionation of Intact Proteins by Reversed-Phase and AnionExchange Chromatography for the Differential Proteomic Analysis of Saccharomyces cerevisiae Jordan T. Stobaugh, Kaitlin M. Fague, and James W. Jorgenson* University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States S Supporting Information *

ABSTRACT: The need for multidimensional separations for bottom-up proteomic analyses has been well demonstrated by many over the past decade. The vast majority of reported approaches has focused primarily on improving the separation once the sample has already been digested. The work presented in this study shows an improvement in multidimensional approaches by prefractionation of intact proteins prior to digestion and separation of the peptides. Two modes of intact protein separation were compared, anion-exchange and reversed-phase, to assess the utility of each mode for the purpose of fractionation. Each of the samples was then enzymatically digested and analyzed by RP-UPLC-MSE. To assess the validity of each approach, baker’s yeast (Saccharomyces cerevisiae) was grown on two different carbon sources, glycerol and dextrose. More proteins were identified by the reversed-phase prefractionation approach (546) than were found by the anion-exchange method (262). As a result, there was much greater coverage of the metabolic pathways of interest for the reversed-phase method than for the anion-exchange method. KEYWORDS: intact protein prefractionation, multidimensional liquid chromatography, reversed-phase chromatography, anion-exchange chromatography, mass spectrometry, label-free proteomics, LC−MS

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INTRODUCTION Emphasis on obtaining qualitative information was typical of proteomic analyses in early proteomics work with much effort being focused solely on the total number of identifications from a given sample. However, much progress has been made with regard to quantitative proteomics in both relative and absolute terms. This has been aided greatly through the use of labeling strategies such as SILAC and iTRAQ.1,2 Significant improvements in mass spectrometric instrumentation and improved data analysis tools have also contributed greatly toward the expansion of quantitative approaches.3 An active area of interest in proteomics is biomarker discovery for use in the diagnosis and treatment of various diseases and conditions with particular interest toward biomarkers for cancer.4 One approach for biomarker discovery is to compare the expression levels of proteins between a sample of interest and a control in a differential proteomic analysis and has been used in the identification of biomarkers for various forms of cancer.5 While the total number of protein identifications is typically reported, a differential proteomic analysis is more concerned with the fold-change in expression levels between samples for proteins of interest, which is especially useful for biomarker discovery. 2D gel electrophoresis (2DE) was traditionally used for differential protein expression analysis. 2DE works by first separating proteins by their isoelectric point, utilizing isoelectric focusing, and then by molecular weight with SDS-PAGE © XXXX American Chemical Society

electrophoresis, with both separations occurring on a polyacrylamide gel. Spots are then excised, and the proteins, which are digested in gel, are analyzed by traditional chemical sequencing techniques or by LC−MS/MS. This method is not without its drawbacks, including a small dynamic range, difficulty in spot picking, and poor resolution of very large, small, acidic, and basic proteins.6 Interfacing 2DE with mass spectrometry is also more difficult than methods utilizing liquid chromatography. 2DE requires more sample handling and is generally more labor intensive than strategies based on liquid chromatography. More typical of proteomic analyses today are bottom-up approaches. In a true bottom-up analysis, the intact proteins are not subject to an initial separation but are instead digested, often by trypsin, and the resultant peptide mixture analyzed by LC−MS/MS.7 While sample complexity is greatly increased due to the digestion, the chromatography of peptides is less problematic than that of intact proteins. Gradients of water and acetonitrile with formic acid as a modifier are typical of peptide separations and can be done on a C18 stationary phase without much in the way of special considerations. Sequencing and database searching programs have also become powerful tools as computing resources continue to improve, allowing for Received: July 27, 2012

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dx.doi.org/10.1021/pr300701x | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

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analysis.17 We independently arrived at many of the same conclusions and utilized a similar approach as Martosella with a few key differences required for our particular sample as it was applied to a label-free differential proteomic analysis of yeast. In this analysis, cytosolic yeast proteins were extracted from cells grown in both dextrose and glycerol-based media. These intact protein samples were then fractionated by either anionexchange or reversed-phase chromatography with each fraction then subject to a trypsin digestion and peptide analysis by UPLC/MSE.

better searching and shorter processing times. Peak widths for peptides are also generally narrower as well, so the increase in complexity is somewhat offset by a greater effective peak capacity. However, for very complex samples, such as cell lysates, the peak capacity for one-dimensional chromatography is insufficient to chromatographically resolve all of the components. The mass spectrometer does provide another dimension of separation; however, even the most advanced mass spectrometers currently available can be overwhelmed by exceedingly complex samples and ultimately benefit from improved chromatographic peak capacity. To overcome the lack of peak capacity, numerous strategies involving multidimensional separations have been employed. One of the most notable is the multidimensional protein identification technology (MudPIT) approach pioneered by Yates.8,9 This method utilizes a biphasic capillary column with cation-exchange as the first dimension and reversed-phase as the second dimension of separation directly coupled to a mass spectrometer through electrospray ionization. Other techniques use two separate capillary columns with modes of operation including cation-exchange followed by reversed-phase as well as high pH reversed-phase followed by a low pH reversed-phase dimension.10 All three of these modes, however, are focused solely on peptides and require a digestion of the sample as the initial step in the analysis. Analysis of intact proteins, top-down proteomics, is a challenging problem in terms of both the chromatography and mass spectrometry and is therefore not as common as methods involving the analysis of peptides. Identification of proteins through mass alone is not considered to be a reliable approach for making the identification due to post-translational modifications that can alter the molecular weight of the analyte. ESI further complicates the problem by attaching multiple charges to a protein requiring deconvolution for the intact mass. If multiple proteins are eluting at the same time, it is frequently observed that only one or two proteins will be deconvoluted.11 For samples with thousands of proteins, such as a cell lysate, and peak capacities for intact protein separations insufficient to resolve that many components, a significant amount of information is lost as a result of competitive ionization and deconvolution. Of course, some mass spectrometers are more adept at handling these challenges than others. However, the cost associated with such instrumentation makes it impractical for many groups.12,13 To take advantage of the benefits from both bottom-up and top-down analyses, multidimensional separations can be utilized to enhance peak capacity by prefractionation at the protein level followed by analysis of the digested fractions. One such technique that has become more prevalent recently is geleluted liquid-fraction entrapment electrophoresis (GELFrEE), which uses tube gels to separate proteins running in an electrophoretic separation.14 Narrow bands have been observed using this instrumentation so long as the gels are not overloaded.13 Work in our lab has focused on implementing solutions using liquid chromatography and has resulted in our determination that prefractionation of intact proteins by liquid chromatography is a good alternative to bottom-up, top-down, or gel prefractionation strategies. This approach was first demonstrated by Martosella et al. in 2005 and was expanded upon with comparisons to multiple techniques by Dowell et al. in 2008.15,16 Other protein fractionation methods by liquid chromatography utilized monolithic columns, which were compared to established bottom-up approaches for peptide

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MATERIALS AND METHOD

Materials

Water, acetonitrile, isopropyl alcohol, and ammonium hydroxide were purchased from Fisher Scientific (Fair Lawn, NJ). Ammonium acetate, ammonium bicarbonate, trifluoroacetic acid, and iodoacetamide were purchased from Sigma-Aldrich Co. (St. Louis, MO). Rapigest SF acid-labile surfactant and bovine serum album were obtained from Waters Corporation (Milford, MA). Dithiothreitol was purchased from Research Products International (Mt. Prospect, IL), and TPCK-modified trypsin was purchased from Pierce (Rockford, IL). Water and acetonitrile were Optima LC−MS grade, and all other chemicals were ACS reagent grade or higher. Sample Preparation

YAPD and YAPG growth media was prepared by combining 6.0 g of yeast extract, 12.0 g of Peptone, 12.0 g of glucose or 5 mL of glycerol, 60 mg of adenine hemisulfate, and 26 600 mL of water and an additional 10 g bacto-agar for media for the plates. S. cerevisiae (BY4741) was the cell line used for analysis. Plates of each growth media were streaked with yeast and incubated until sizable colonies were obtained. This process required two days for dextrose and four days for glycerol-based media. A single colony was then used to inoculate a 150 mL small-scale culture, which were grown to an OD600 (optical density 600 nm) greater than 2.0. The small-scale culture was then used to innoculate the 2 L (in a 4 L flask) prep scale batches. Both the glycerol and dextrose-based media samples were harvested when the OD was 2.0. For the glyercol-based media, significantly more time was required to reach this end point. Cells were centrifuged at 7000g in a Sorvall GS-3 rotor for 30 minutes until pelleted. Cells were then stored at −80 °C until processed. Cells were resuspended by pipet in 2 volumes of 50 mM ammonium bicarbonate with protease inhibitors present (Pierce protease inhibitor tablets, 88 661) prepared to manufacturer’s recommendations. A homogenate was prepared by eight passes through a chilled french press cell dropwise at 20 000 psi. The homogenate was centrifuged (Beckman JA20 rotor, 30 000g, 20 min, 4 °C), and a cytosolic fraction was prepared from the cleared lysate by ultracentrifugation at 120 000g for 90 min at 4 °C. Cytosolic fractions were determined to be between 10 and 13 mg/mL of total protein using the BioRad (Hercules, CA) protein assay with BSA standard. Immediately prior to analysis, each fraction was diluted with 25 mM ammonium bicarbonate to provide an equivalent protein concentration in all samples. Intact Protein Prefractionation

The intact proteins were separated by strong anion exchange and reversed phase. The first prefractionation separation was performed using anion-exchange chromatography (Waters B



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BioSuite Q SAX 10 μm, 7.5 × 75 mm, 50 °C). The mobile phase compositions and gradient profile are shown in Table 1, and two-minute wide fractions were collected from 2 to 82 min and every other fraction pooled, yielding 20, four-minute wide fractions.

Mobile phase A was Optima-grade water with 0.1% formic acid (Fisher), and mobile phase B was Optima-grade acetonitrile with 0.1% formic acid (Fisher). At a flow rate of 300 nL/min, a 90 min gradient from 5 to 40% B was used to separate the peptides, followed by a 5 min column wash at 85% B, after which the mobile phase was returned to 5% B. An amount of 2 μL of sample was injected per run for an average column load of approximately 1 μg of digest protein per run. The outlet of the RPLC column was directly connected to an uncoated fused silica nanospray emitter with a 20 μm ID and a 10 μm tip (New Objective, Woburn, MA) operated at 2.7 kV. Data-independent acquisition or MSE scans were performed, and the instrument was set to perform parent ion scans from m/z 50 to 1990 over 0.6 s at 5.0 V. The collision energy was then ramped from 15 to 40 V over 0.6 s. All MS data are available at http://jjorg.web. unc.edu/.

Table 1. Chromatographic Conditions for the AnionExchange Prefractionation of Intact Proteins time (min)

25 mM ammonium acetate, pH 9.0 (% A)

1 M ammonium acetate, pH 9.0 (% B)

0 60 90 90.1

100 0 0 100

0 100 100 0

The second prefractionation of intact proteins was performed on a 4.6 × 250 mm PLRP-S column with 5 μm particles (Agilent, Santa Clara, CA) heated to 80 °C. Again, 4 mg of total protein was injected onto the column. The mobile phase compositions and gradient profile are shown in Table 2.

Peptide Data Processing

The peptide LC−MS/MS data were processed using ProteinLynx Global Server 2.5 (Waters). The MSE spectra were searched against a database of known yeast proteins from the Uni-Prot protein knowledgebase (www.uniprot.orgt) with a 1X randomized sequence appended to the end. The false discovery rate was set to 100% to yield data compatible for further processing. After the database search was complete, the results were imported into Scaffold 3.1.4.1 (Proteome Software, Portland, OR). The minimum protein probability, peptide number, and peptide probability filters were set to 99.0%, 3, and 95%, respectively, which gave a 3.4% protein false discovery rate. Peptides matching multiple proteins were exclusively assigned to the protein with the most evidence. The spectral counts for each peptide assigned to a protein were summed to give the quantitative value of that protein. The value was normalized by multiplying the average total number of spectra, for all yeast samples grown on the same media, divided by the individual sample’s total number of spectra.18,19 A Fisher’s exact test was performed on the triplicate samples. Proteins with a p-value less than 0.050 between the two yeast samples and a fold change greater than 1.5 were considered to be differentially expressed.

Table 2. Chromatographic Conditions for the ReversedPhase Prefractionation of Intact Proteins time (min)

90:5:5 H2O:ACN:IPA + 0.2% TFA (% A)

50:50 ACN:IPA + 0.2% TFA (% B)

0 2 5 40 45 45.1 50 50.1

100 100 75 50 35 0 0 100

0 0 25 50 65 100 100 0

One-minute wide fractions were collected from 2 to 42 min and every other fraction pooled, yielding 20, two-minute wide fractions. Each prefractionation method was run in triplicate. Fractions were stored at −80 °C until needed.

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Protein Digestion and Peptide LC−MS/MS

Fractions were transferred to microcentrifuge tubes and then lyophilized and reconstituted in 25 μL of 50 mM ammonium bicarbonate. Three microliters of 6.67% (w/v) RapiGest SF in buffer were added (15 min, 80 °C) to denature the proteins. The proteins were reduced by adding 1 μL of 100 mM dithiothreitol (30 min, 60 °C) and then alkylated with 1 μL of 200 mM iodoacetamide (30 min, room temperature, protected from light). The proteins were then digested by adding 10 μL of 320 ng/μL TPCK-modified trypsin in 50 mM ammonium bicarbonate (overnight, 37 °C). Once the digestion was complete, the RapiGest SF was degraded using 44 μL of 1% (v/v) trifluoroacetic acid (2 h, 60 °C). The fractions were centrifuged for 20 min at 14 000g to pellet the hydrolyzed surfactant, after which they were ready for analysis. The samples were transferred to LC vials and spiked with 4.21 μL of a 1 pmol/L internal standard Bovine serum albumin digest (Waters). Each fraction was analyzed using capillary RPLC−MS/MS using a Waters nanoAcquity/QTOF Premier system. The separations were performed on a 250 mm × 75 μm inside diameter (ID) capillary column packed with 1.7 μm silica bridged-ethyl particles with a C18 stationary phase (Waters).

RESULTS AND DISCUSSION

Prefractionation of intact proteins for bottom-up analysis resulted in a total of 40 fractions being collected per separation mode. Analyzing all 40 fractions would require more than 240 h of analysis time per intact protein sample, as the digested fractions were run in triplicate. To reduce the analysis time to a more manageable amount, it was determined that every other fraction would be pooled after digestion. Additionally, each intact protein separation for the reversed-phase prefractionation approach was completed three times, unlike in the case of anion exchange where only the peptide fractions were run three times. Each of the resulting peptide fractions was then analyzed by UPLC−MSE. By plotting the results of the peptide data in a two-dimensional plot, as shown in Figure 1, it can be observed that this multidimensional approach where proteins are enzymatically digested between the first and second dimensions of separation results in an orthogonal separation as the available separation space has been well utilized. From these plots, it can be observed that the prefractionation by reversed-phase chromatography utilized a greater proportion of the available separation space than did the anion-exchange prefractionation approach as peptides are more uniformly distributed for the C



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window would have only resulted in broader peaks without an increase in resolution. Reversed-phase chromatography was explored as an alternative to the anion-exchange method. Greater resolution for the reversed-phase method was expected as reversed-phase chromatography typically yields higher-resolution separations than ion exchange for proteins. After exploring a few different column chemistries, a PLRP-S column, comprised of polystyrene-divinyl benzene particles, was selected for use for prefractionation of intact proteins by reversed-phase due to the rugged nature of the material and a high-temperature limit, which was advantageous when working with protein samples prone to precipitation. Gradients of water and acetonitrile were found to be insufficient to prevent protein precipitation; therefore, mobile phase B was comprised of 50% acetonitrile and 50% isopropanol with 0.2% TFA. Mobile phase A was 90% water, 5% acetonitrile, and 5% isopropanol with 0.2% TFA. The use of isopropanol in combination with elevated temperatures (80 °C) has been shown to improve the resolution of intact protein separations.15,20 The gradient used for fraction collection contained an initial hold to trap the proteins on the head of the column with a quick ramp to elution conditions where the gradient was then flattened for fraction collection. This method provided for separations with almost no ghosting and reproducible results as observed by the intact protein separations of both the dextrose- and glycerol-based yeast separations run in triplicate (Supporting Information, Figure 2). Similarly to the anion-exchange method, a substantial signal was observed at the dead time in the UV data; however, this did not transition into a long delay, and instead peaks were observed more consistently throughout the gradient. Furthermore, the resolution of the peaks was significantly improved in the reversed-phase separation with many more peaks observed overall. Lastly, for both approaches, fraction collection was continued well beyond the last observed peak and until the baseline stabilized in an effort to collect as many proteins as possible.

Figure 1. Two-dimensional chromatograms of the dextrose yeast separation. The prefractionation retention time is along the left axis with the corresponding protein fraction denoted on the right axis. The peptide separation is shown along the x-axis. The base peak intensity is expressed in the z-direction with darker colors representing more intense peaks. Prefractionation was completed by (a) anion exchange and (b) reversed-phase chromatography. Intensity scales are identical.

reversed-phase approach with respect to the anion-exchange approach. Qualitative results from the UV data of the first dimension provided good initial insight without the substantial investment in time required by the digestion and bottom-up analysis of each fraction. For both the dextrose- and glycerol-based yeast samples, the anion-exchange separation exhibited a substantial absorption signal in the UV data at the dead time followed by a lull in elution until the ionic strength of the mobile phase had increased sufficiently to elute proteins. The large signal occurring at the dead time was assumed to be proteins not retained by the anion exchange sorbent (Supporting Information, Figure 1). Fraction collection continued until all proteins were assumed to have been eluted owing to a lack of peaks in the UV data and a return to baseline conditions. The observed elution profile was not completely unexpected as some proteins will not be bound by the anion-exchange resin, whereas the majority will and only elute once the gradient increases sufficiently in ionic strength to cause a change in the retention. Attempts were made to lower the ammonium acetate concentration to prevent proteins from eluting in the dead time; however, precipitation of the proteins prevented a further reduction in ionic strength, and a balance had to be maintained between starting conditions and sample solubility. An initial concentration of 25 mM ammonium acetate, pH 9.0, was determined to be an appropriate concentration given the constraints. Further flattening of the gradient during the elution

Protein Fractionation

A more quantitative look at the prefractionation strategies was possible once all of the fractions had been digested and analyzed by UPLC−MSE. In Figure 2, nonunique protein identifications per fraction were represented by the lighter shading in a bar graph for both separations. A nonunique protein was defined as any protein found within a given fraction; thus, if a protein were to be found in multiple fractions it would be counted in each fraction. The number of proteins found per fraction from the anion exchange prefractionation mimics the general trends observed from the UV data, with proteins found initially followed by a lull and then more identifications, as the gradient progressed. In fractions 1 and 2, 77 nonunique proteins were observed, whereas the following three fractions contained a total of 38 nonunique protein hits. For the reversed-phase separation, there was again a large UV absorption signal initially, which did not drop off as quickly as for the anion-exchange separation. The results from the protein identifications, however, were much different with only 11 nonunique identifications in the first three fractions in total. Another area of interest as it relates to the UV data and overall protein identifications occurs toward the end of fraction collection. In both prefractionation strategies, the UV trace decreased significantly over the last five fractions collected. If only nonunique protein identifications were taken into D



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fraction collection was terminated after 44 min as the baseline had stabilized, and no peaks were observed after 32 min (fraction 15). Fractions 16−20 only contributed 33 more unique identifications for the reversed-phase separation and only 16 additional for the anion-exchange prefractionation at a cost of 30 h analysis time per method including replicate analysis. To further evaluate the efficiency of the fractionation, we looked at the number of fractions a unique protein was found in and plotted the results for all unique proteins from both the anion-exchange and reversed-phase prefractionation approaches. The number of fractions a protein was spread across gave us insight into the peak widths in the protein separation even though it could not be directly calculated from the UV data. Looking at raw numbers, there were more unique proteins found in all cases by the reversed-phase method. Given that there were more than twice as many proteins identified by this method, this is not surprising. When normalized, however, the fractions per protein results are consistent across both methods as shown in Figure 4C. Since the majority of proteins, 60% and 61% for reversed phase and anion exchange, respectively, is being found in only one fraction, this indicates that the width of each fraction was more than sufficient to capture the entire peak as it eluted. Inevitably, proteins will elute during a fraction change, resulting in a significant number, 20% and 18%, respectively, being found in two fractions. Somewhat surprising was that 20% of the identified proteins for each prefractionation method were found spread across three or more fractions, indicating that these proteins were eluting over a larger portion of the gradient, demonstrating the difficult nature of intact protein separations. One possible explanation for this is a variety of post-translational modifications (PTMs), which would change the retentivity of the proteins. For a given protein that may be present with differing PTMs, the resulting difference in retention as a result of the variation in modifications could allow for the identification of this protein across many fractions. Once digested, the peptides used to identify the protein would correctly indicate that the protein was found in multiple fractions. If the peptides used in the identification contained the post-translational modification responsible for the shift in retention, then it would be possible for one to determine that the reason for a protein eluting over a large number of fractions was due to PTMs. If these peptides containing the PTMs were not identified, however, then it would be difficult to determine why a protein eluted over a large number of fractions. In total, there were 784 and 345 unique protein identifications from the reversed-phase and anion-exchange prefractionation methods, respectively, which comprise the data observed in the unique identifications in Figure 2. Roughly 25% of these proteins were only identified in one of three replicate runs and were therefore excluded from any potential differential analysis. For the purpose of a differential comparison, a protein must have been identified with a confidence of 95% by Scaffold 3.3 in at least two of three replicate runs. With this stricter criterion, the total identifications were reduced to 546 and 262 for the reversed-phase and anion-exchange prefractionation methods, respectively. Of the 262 proteins identified by the anion-exchange method, 220 were found to be in common with the reversed-phase method and 42 found only by anionexchange prefractionation, while 326 were found solely by reversed-phase (Figure 3). Protein hits were counted as a unique identification if found with a confidence greater than

Figure 2. Total number of protein identifications for each fraction is shown in light gray. Plotting the data in this way is useful as it gives an idea as to what is eluting off of the LC column in each fraction and the complexity of the sample reaching the mass spectrometer. However, for the purpose of determining overall protein identifications, it is more convenient to represent the data by only plotting proteins in the fraction of greatest intensity, as determined through Scaffold 3.3. Fewer identifications were made by the anion-exchange method (a) than by the reversed-phase method (b). For both intact protein separations, a few new unique proteins were identified in the final five fractions. The fraction of unique proteins was also plotted as a function of the number of fractions a unique protein is identified in (c). Both anion-exchange and reversed-phase prefractionation strategies exhibit similar behavior when compared on the basis of gradient fractionation. The majority of proteins (60%) elute in only one fraction, indicating that the fractions were approximately equal to the width of a peak.

consideration, shown in the more lightly shaded region of Figure 2, it would appear as though fraction collection was terminated prematurely in both cases and especially so for the reversed-phase separation, which is not suggested by the UV data. However, by counting a protein only in the fraction containing its most intense spectral counts, as determined through Scaffold, it was shown that only a small number of proteins were uniquely identified in the last five fractions. Had fraction collection been stopped at fraction 15, reducing the number of bottom-up samples and therefore reducing overall analysis time, the overall productivity of the analysis as measured in protein identifications per hour would have been improved. Specifically for the reversed-phase separation, E



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kDa.21 Another way to represent this data is to plot the mass of a protein against the fraction in which it eluted for all of the proteins identified to better visualize the results (Figures 4c,d). This provides for a qualitative inspection lending insight into how well the gradient space of the first-dimension prefraction method is being utilized as well as the molecular weight range of identified proteins. The substantial increase in proteins identified by the reversed-phase prefractionation approach is most evident between 10 and 40 kDa and can be observed in Figure 4b. One can also see the increase in the number of proteins found by reversed-phase prefractionation around the 100 kDa mark. With regard to the chromatography, the same general elution patterns can be discerned as observed in the UV data, although a drift in molecular weight toward larger proteins was observed between fractions 4 and 15 for the reversed-phase separation.

Figure 3. Reversed-phase prefractionation method identified 546 proteins in 2/3 replicate runs, whereas there were only 262 proteins identified in 2/3 replicate runs of the peptide fractions. Only 16% of the proteins identified by anion exchange were not identified by the reversed-phase approach. Twenty fractions were analyzed by each method to allow for a uniform comparison based on gradient fractionation.

Differential Comparison for Reversed-Phase and Anion-Exchange Fractionation Strategies

The reversed-phase method exhibited greater overlap between the dextrose and glycerol yeast samples than the anionexchange method with 56% of the total proteins identified found in common between the dextrose and glycerol yeast samples (Figure 5a). For the anion-exchange method, there was a 36% overlap of total proteins identified between the two samples (Figure 5b). As a result, the anion-exchange method was found to have a substantially increased number of proteins that could potentially be considered as differential proteins with nearly half of the proteins identified in each sample identified uniquely. Upon closer examination of the differential proteins, it was observed that for many of these identifications the intensity of these proteins was low, with only a few spectral counts. For proteins considered to be differentially expressed,

95% by Scaffold with a minimum of three peptides, each with a confidence greater than 95%. Molecular Weight Distribution of Identified Proteins

The distribution of proteins identified based on molecular weight was another area of interest for comparison between the two modes of prefractionation. When plotted as a histogram with 10 kDa bins from 0 to 250 kDa, the majority of proteins were identified between 10a and 40 kDa (Figure 4a,b). No significant bias was observed as the median molecular weight of proteins identified by the reversed-phase and anion-exchange prefractionation methods was determined to be 38.0 and 37.6 kDa, respectively, with the median length of a baker’s yeast protein reported to be 385 amino acids or approximately 42.4

Figure 4. There was no bias associated with the molecular weight of the intact proteins identified by either prefractionation method. The median mass of proteins identified was 37.6 kDa for anion exchange (a) and 38.0 kDa for reversed phase (b). The distribution of protein masses across the intact protein fractions can be observed in (c) for anion exchange and in (b) for reversed phase. F



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detection for the anion-exchange prefractionation method was adversely affected. Of the proteins involved in the metabolic pathways of interest, with high-confidence peptide assignments, and found to be differentially expressed, clear trends emerged with regard to the effectiveness of intact protein prefractionation by the reversed-phase method in comparison to the anion-exchange separation. Table 3 lists many of these proteins with the average number of peptides used in the identification as well as the average coverage percentage as determined by Scaffold for both the dextrose and glycerol samples. For the dextrose sample, 23 peptides were found per protein on average for the differentially expressed proteins fractionated by reversed phase and only 12 for the anion-exchange prefractionation strategy with the coverage being 53% and 33%, respectively. A similar trend was observed for the glycerol sample with 27 peptides and 60% coverage for the reversed-phase method and only 13 peptides and 36% coverage on average from the anion-exchange method for the differential identifications. The literature shows that growing yeast on different carbon sources affects expression of metabolic enzymes. The differential protein intensities measured by the methods described here follow the trends in protein expression predicted by the literature.22 A stronger correlation exists between the literature and the results from the reversed-phase prefractionation method than with the anion-exchange prefractionation method due to the greater number of protein identifications as well as greater intensity as determined by spectral counts with the reversed-phase prefractionation method. Several metabolic pathways are altered when yeast is grown on glycerol versus its preferred carbon source, dextrose. Glycolysis, gluconeogenesis, glycerol catabolism, glycerolneogenesis, fermentation, tricarboxylic acid cycle (TCA), glyoxylate cycle, and the pentose phosphate pathway will be discussed in more detail (Figure 6). The complete set of results indicating fold changes for proteins meeting the acceptance criteria and confidence can be found in the Supporting Information. Glycolysis is the digestion of glucose to pyruvate, which can then be converted into energy through the TCA cycle, glyoxylate cycle, or fermentation. When glucose is not present, the cell undergoes gluconeogenesis, which is the formation of glucose from pyruvate. Many of the same proteins are involved in glycolysis and gluconeogenesis. As expected, there is no general trend in the differential expression of these proteins as they are active in yeast grown on both media sources. The proteins involved in both these processes were identified by both methods. The one exception is F16P which transforms fructose-1,6-P to fructose-6-P during gluconeogenesis, while K6PF1 is involved in the reverse reaction during glycolysis. F16P protein was found to be up-regulated in the reversedphase fractions of the glycerol sample, but this protein was below the limit of quantification in the anion-exchange fractions which is evidence of greater sensitivity being achieved by the reversed-phase prefractionation. Analogous to glycolysis and gluconeogenesis are glycerol metabolism, which converts glycerol into pyruvate, and glycerolneogenesis, which converts pyruvate into glycerol. For the yeast grown on glycerol, it is predicted that the proteins used in glycerol catabolism such as GLPK and GPD1 would be up-regulated,23,24 while the proteins used in glycerolneogenesis, such as GPP1 and GPP2, would be down-regulated.25 This phenomenon is observed in the reversed-phase fractions, but

Figure 5. (a) Reversed-phase prefractionation approach showed greater overlap between the two samples than either anion-exchange fractionation approach and significantly more proteins overall. While the samples were grown on different carbon sources, a significant amount of agreement is expected between the two. (b) Greater variability in the identified proteins was observed between the two samples when prefractionated by anion-exchange chromatography. In general, proteins identified by the anion-exchange method were less intense than by the reversed-phase method, suggesting that the decreased overlap between the two samples may be due in part to poor recovery.

one must question the extent of the differential expression for proteins with low spectral counts being identified solely in the glycerol- or dextrose-based samples. This is because at the low intensity levels reported it is possible that, for the sample where a given protein was not identified, the limit of detection for the analysis may play a greater role in the differential classification than what is the result of differences in the biological processes. Impacting the limit of detection for the anion-exchange prefractionation strategies is the problem of protein recovery. With our particular cell lysates, it was found that the inlet frit of the anion-exchange column would clog after repeated injections, creating a substantial increase in back pressure requiring routine cleaning to maintain the column. It is probable that a closer look at the anion-exchange prefractionation would confirm recovery as being an issue with this method of prefractionation. Clogging of inlet frits was not found to be problematic for the PLRP-S column with no increase in back pressure observed after repeated injections. Taking this into consideration, along with higher signal intensities for samples from reversed-phase prefractionation, protein recovery was most likely critically important to the improved performance of the reversed-phase method over anion-exchange. With proteins likely precipitating on the inlet frit of the anion-exchange column, a smaller amount of the sample was available for enzymatic digestion, and with a resulting decrease in peptide concentrations, the limit of G



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Table 3. Number of Peptides Used in an Identification as Well as the Coverage Percentage of the Proteome are Shown for Both Anion-Exchange and Reversed-Phase Prefractionation of Proteins Determined to Be Involved in the Metabolic Pathways of Interest and Differentially Expressed dextrose

glycerol

Pep

% Cov

Pep

% Cov

name

accession

AX

RP

AX

RP

AX

RP

AX

RP

6-phosphofructokinase subunit α 6-phosphogluconate dehydrogenase acetyl-coenzyme A synthetase 1 aconitrate hydratase, mito alcohol dehydrogenase 1 alcohol dehydrogenase 2 alcohol dehydrogenase 3, mito alcohol dehydrogenase 6 aldehyde dehydrogenase 5, mito citrate synthase, mito dihydrolipoyl dehydrogenase, mito enolase 1 enolase 2 fructose-bisphosphate aldolase fumarate hydratase, mitoc fumarate reductase glucokinase-1 glucose-6-phosphate isomerase glyceraldehyde-3-P dehydrogenase 1 Glyceraldehyde-3-P dehydrogenase 2 glyceraldehyde-3-P dehydrogenase 3 hexokinase-1 hexokinase-2 isocitrate lyase K-activated aldehyde dehydrogenase malate dehydrogenase, cyto malate dehydrogenase, mito phosphoenolpyruvate carboxykinase phosphoglycerate kinase phosphoglycerate mutase 1 pyruvate carboxylase 1 pyruvate decarboxylase isozyme 1 pyruvate dehydrogenase E1 comp β pyruvate kinase 1 succinyl-CoA ligase subunit α succinyl-CoA ligase subunit β transketolase 1 transketolase 2 triosephosphate isomerase average

K6PF1 6PGD1 ACS1 ACON ADH1 ADH2 ADH3 ADH6 ALDH5 CISY1 DLDH ENO1 ENO2 ALF FUMH FRDS HXKG G6PI G3P1 G3P2 G3P3 HXKA HXKB ACEA ALDH4 MDHC MDHM PCKA PGK PMG1 PYC1 PDC1 ODPB KPYK1 SUCA SUCB TKT1 TKT2 TPIS

1.0 16.7 13.7 1.3 13.3 35.7 3.3 3.7 7.0 10.0 11.7 8.0 9.0 7.7 40.0 13.0 12.3 1.0 32.0 2.7 3.0 11.7 11.7

26.3 32.7 8.3 25.3 19.0 2.7 2.7 7.3 20.7 54.0 30.7 10.7 2.7 36.3 29.0 24.0 10.7 19.0 33.3 6.0 53.3 27.0 6.0 53.0 2.7 62.0 13.7 22.7 21.3 22.9

1.6 54.0 30.0 6.9 42.0 57.0 6.9 13.0 19.3 23.7 44.3 71.3 25.7 38.0 77.0 46.7 19.3 4.1 76.0 15.1 7.4 52.0 33.2

37.3 66.0 13.7 66.0 40.7 7.2 14.6 23.5 78.7 88.3 76.7 33.0 7.8 69.0 52.3 84.0 88.0 54.0 79.3 31.0 87.0 80.0 9.6 80.0 8.1 87.7 52.7 42.7 85.0 53.2

0.7 7.0 13.3 5.7 17.7 28.3 1.3 1.7 0.7 2.0 15.0 44.0 9.7 10.3 10.0 30.0 25.3 13.3 9.7 4.7 10.0 4.0 36.3 10.7 21.3 1.7 38.3 17.3 6.3 12.0 4.7 32.3 15.0 2.0 3.7 1.7 19.7 13.2

26.7 38.0 38.0 34.3 22.3 38.3 4.0 1.0 26.7 37.3 24.7 51.3 32.7 18.0 7.7 39.0 37.3 36.0 22.3 10.3 35.3 29.3 11.7 54.7 16.3 24.0 36.7 49.3 22.3 15.0 47.3 4.3 57.3 21.7 23.7 24.3 5.0 19.7 27.5

1.3 20.0 24.0 11.9 53.7 63.0 5.7 8.6 3.9 7.4 67.3 70.3 21.3 34.0 28.3 56.3 63.0 58.7 81.7 13.0 34.7 8.7 66.0 35.3 70.3 3.7 79.3 66.7 8.7 24.3 14.3 75.7 61.7 6.9 8.9 3.1 86.3 36.4

34.3 77.7 52.0 48.7 65.0 71.3 13.8 6.1 54.0 77.3 78.0 85.3 71.0 48.0 22.3 71.3 69.3 81.0 85.7 91.7 79.3 81.0 30.3 80.7 62.7 71.3 60.7 82.7 75.3 19.3 71.0 16.3 84.0 82.0 46.3 42.7 12.0 84.7 60.2

these proteins were not detected in the anion-exchange fractions. After its biogenesis, pyruvate is fermented into ethanol if there is an excess amount of glucose present. A protein complex is formed by PDC1, PDC5, and PDC6.26 This complex is involved in the conversion of pyruvate to acetaldehyde during fermentation. These three subunits were detected in the reversed-phase fractions with PDC5 and PDC6 being upregulated in the dextrose sample. Only PDC1 was identified by anion exchange, and it was similarly determined to be upregulated in the dextrose sample. In the absence of glucose, pyruvate enters the TCA or glyoxylate cycle.27 Additionally, any ethanol that may be present is converted into acetate to be used in the TCA or glyoxylate cycle.24,28−31

In these pathways, 49 of 52 proteins were identified in the reversed-phase fractions with 28 being up-regulated in the glycerol sample, 6 up-regulated in the dextrose sample, and 15 identified in both, but not differentially. In the anion-exchange fractions, only 37 of 52 proteins were identified with 14 being up-regulated in the glycerol sample, 3 in the dextrose sample, and 20 identified in both, but not differentially. Fewer differential proteins were observed in the anion-exchange fractions because many of the proteins were lower in intensity and the run-to-run variation was great enough to obscure classification as a differential protein. The metabolic pathways for yeast grown on glycerol occur in the mitochondria, while fermentation occurs in the cytoplasm. When looking at the data from the reversed-phase prefractionation method, our results show that out of 100 mitochondrial proteins identified 37 were H



Article

Figure 6. Up-regulation of the TCA cycle and the glyoxylate cycle are much more evident from the reversed-phase prefractionation approach. Many more proteins were identified by the reversed-phase method, and these additional identifications were needed to form conclusions. The upregulation of proteins in these pathways meets expectations given the nature of the differential sample.

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up-regulated in the glycerol sample, while only 16 were upregulated in the dextrose sample. The pentose phosphate pathway takes glucose and transforms it into ribulose-5-phosphate, which is used in the formation of ribosomes and subsequently DNA synthesis. Cells grown in a glucose-deficient environment will break down the ribulose-5-phosphate to be used in the TCA cycle. Therefore, an abundance of ribosomal proteins should exist in the yeast grown on dextrose. Again, using the data from the reversedphase prefractionation, the results indicate 32 out of the 55 ribosomal proteins identified were up-regulated in the dextrose sample, while only 3 were up-regulated in the glycerol sample. Data supporting this finding can be found in the Supporting Information.

CONCLUSIONS

Fractionation of intact proteins results in more of the peptides for a given protein being confined to fewer fractions. The combination of peptides for a protein being found in a narrower region of the separation space along with the reduction in sample complexity from the hundreds, if not thousands, of other proteins present in the original sample can work to increase the confidence in protein identifications. This is in opposition to total bottom-up methods employing multidimensional separations for the analysis of peptides in both dimensions where peptides from a given protein could be found across a wide range of fractions. Fractionation of intact proteins by either anion-exchange or reversed-phase chromaI



Article

approaches hopefully will serve as an alternative strategy to bottom-up approaches, both shotgun and multidimensional, as proteomic analyses move in the direction of intact protein analysis.

tography allowed for greater peak capacity in an environment where there is a need, as there are approximately 5500 proteins encoded by the yeast genome.32 The reversed-phase method was determined to be particularly powerful as temperatures in excess of 80 °C were utilized to improve recovery and peak shape, and greater recovery allowed for greater proteome coverage, which enabled the differential comparison. Many of the proteins involved in the metabolic pathways investigated within this work were only found by the reversed-phase method. These methods also allowed for milligram quantities of protein to be analyzed as opposed to microgram quantities common to gel electrophoresis-based methods. Greater sample loading allowed for greater flexibility with peptide analysis as there was a greater volume of sample available for analysis as well as a greater amount of peptides from less abundant proteins, allowing their identification. More importantly, however, is that the ability to load a greater amount of protein allows for the possibility of finding proteins of lower abundance. In many respects, this type of analysis is analogous to a tandem mass spectrometric analysis. In the mass spectrometer, the sample is introduced, selected (by mass), and fragmented by collision-induced dissociation, and the fragments are detected and analyzed to elucidate the identity of the species in question. The liquid chromatographic prefractionation approach is quite similar. The sample is injected onto the first column where it is selected based on the separation mechanism chosen for this dimension. The fractions containing separated proteins are then subjected to a reaction that creates many fragments through enzymatic digestion. These fragments are then analyzed to determine the identity of the unknown species, in this case, proteins. While the MS/MS analysis is clearly an online format and the proposed prefractionation approach is not, coupled offline separations have long been considered multidimensional separations. In these situations, however, the sample is usually not modified between the separation dimensions to the extent in which the sample is modified in this analysis. With over 120 h needed to complete the triplicate analysis for a single sample and twice that to make a differential comparison, this method does require a significant investment in time. A parameter to be explored in the future is the extent of fractionation required to generate useful data. The effect of fractionation has been studied previously by many groups and will continue to be studied as there is always a balance to be maintained between analysis time and proteome coverage.33 If proteins of interest could be identified and quantified by only splitting the intact protein separation into 10 fractions, then this would be of great benefit to the investigator. Alternatively, owing to the improved resolution of the reversed-phase method, one could arguably benefit from increased fractionation, depending on the goals of the investigator. What is likely a more prudent approach to explore is to base the fractionation off of the UV data, rather than applying the same fractionation scheme of equally sized fractions to the entire gradient. Areas where there is significant signal intensity in the UV data could be more finely fractionated. The end of the gradient could be relegated to one large fraction, as there were few new protein identifications made during this time, yet a significant amount of analysis time was required when evenly fractionating the gradient. While the results, in terms of biological significance, were not particularly surprising nor novel, the utilization of intact protein fractionation and the comparison of fractionation

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ASSOCIATED CONTENT

S Supporting Information *

Supplemental Figures 1 and 2 and additional experimental details. This material is available free of charge via the Internet at http://pubs.acs.org

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: 919-966-5071. Fax: 919-962-2388. Notes

The authors declare the following competing financial interest(s): Waters Corporation provided funding for this research.

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ACKNOWLEDGMENTS Assistance with yeast cell culture was provided courtesy of Dr. Dorothy Erie and Vanessa DeRocco at the University of North Carolina at Chapel Hill. Funding was provided by Waters Corporation.

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REFERENCES

(1) Wiśniewski, J. R.; Mann, M. Consecutive Proteolytic Digestion in an Enzyme Reactor Increases Depth of Proteomic and Phosphoproteomic Analysis. Anal. Chem. 2012, 84 (6), 2631−2637. (2) Kocher, T.; Pichler, P.; Schutzbier, M.; Stingl, C.; Kaul, A.; Teucher, N.; Hasenfuss, G.; Penninger, J. M.; Mechtler, K. High Precision Quantitative Proteomics Using iTRAQ on an LTQ Orbitrap: A New Mass Spectrometric Method Combining the Benefits of All. J. Proteome Res. 2009, 8 (10), 4743−4752. (3) Li, Z.; Adams, R. M.; Chourey, K.; Hurst, G. B.; Hettich, R. L.; Pan, C. Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos. J. Proteome Res. 2011, 11 (3), 1582−1590. (4) Qian, W.-J.; Monroe, M. E.; Liu, T.; Jacobs, J. M.; Anderson, G. A.; Shen, Y.; Moore, R. J.; Anderson, D. J.; Zhang, R.; Calvano, S. E.; Lowry, S. F.; Xiao, W.; Moldawer, L. L.; Davis, R. W.; Tompkins, R. G.; Camp, D. G.; Smith, R. D. Quantitative Proteome Analysis of Human Plasma following in Vivo Lipopolysaccharide Administration Using 16O/18O Labeling and the Accurate Mass and Time Tag Approach. Mol. Cell. Proteomics 2005, 4 (5), 700−709. (5) Roy, S. M.; Anderle, M.; Lin, H.; Becker, C. H. Differential expression profiling of serum proteins and metabolites for biomarker discovery. Int. J. Mass Spectrom. 2004, 238 (2), 163−171. (6) Monteoliva, L.; Albar, J. P. Differential proteomics: An overview of gel and non-gel based approaches. Briefings Funct. Genomics Proteomics 2004, 3 (3), 220−239. (7) Yates, J. R.; Ruse, C. I.; Nakorchevsky, A. Proteomics by Mass Spectrometry: Approaches, Advances, and Applications. Annu. Rev. Biomed. Eng. 2009, 11 (1), 49−79. (8) Wolters, D. A.; Washburn, M. P.; Yates, J. R. An Automated Multidimensional Protein Identification Technology for Shotgun Proteomics. Anal. Chem. 2001, 73 (23), 5683−5690. (9) Washburn, M. P.; Ulaszek, R.; Deciu, C.; Schieltz, D. M.; Yates, J. R. Analysis of Quantitative Proteomic Data Generated via Multidimensional Protein Identification Technology. Anal. Chem. 2002, 74 (7), 1650−1657. (10) Gilar, M.; Olivova, P.; Daly, A. E.; Gebler, J. C. Twodimensional separation of peptides using RP-RP-HPLC system with different pH in first and second separation dimensions. J. Sep. Sci. 2005, 28 (14), 1694−1703. J



Article

(11) Staub, A.; Guillarme, D.; Schappler, J.; Veuthey, J.-L.; Rudaz, S. Intact protein analysis in the biopharmaceutical field. J. Pharm. Biomed. Anal. 2011, 55 (4), 810−822. (12) Tran, J. C.; Zamdborg, L.; Ahlf, D. R.; Lee, J. E.; Catherman, A. D.; Durbin, K. R.; Tipton, J. D.; Vellaichamy, A.; Kellie, J. F.; Li, M.; Wu, C.; Sweet, S. M. M.; Early, B. P.; Siuti, N.; LeDuc, R. D.; Compton, P. D.; Thomas, P. M.; Kelleher, N. L. Mapping intact protein isoforms in discovery mode using top-down proteomics. Nature 2011, 480 (7376), 254−258. (13) Vellaichamy, A.; Tran, J. C.; Catherman, A. D.; Lee, J. E.; Kellie, J. F.; Sweet, S. M. M.; Zamdborg, L.; Thomas, P. M.; Ahlf, D. R.; Durbin, K. R.; Valaskovic, G. A.; Kelleher, N. L. Size-Sorting Combined with Improved Nanocapillary Liquid Chromatography− Mass Spectrometry for Identification of Intact Proteins up to 80 kDa. Anal. Chem. 2010, 82 (4), 1234−1244. (14) Tran, J. C.; Doucette, A. A. Gel-Eluted Liquid Fraction Entrapment Electrophoresis: An Electrophoretic Method for Broad Molecular Weight Range Proteome Separation. Anal. Chem. 2008, 80 (5), 1568−1573. (15) Martosella, J.; Zolotarjova, N.; Liu, H.; Nicol, G.; Boyes, B. E. Reversed-Phase High-Performance Liquid Chromatographic Prefractionation of Immunodepleted Human Serum Proteins to Enhance Mass Spectrometry Identification of Lower-Abundant Proteins. J. Proteome Res. 2005, 4 (5), 1522−1537. (16) Dowell, J. A.; Frost, D. C.; Zhang, J.; Li, L. Comparison of TwoDimensional Fractionation Techniques for Shotgun Proteomics. Anal. Chem. 2008, 80 (17), 6715−6723. (17) Melchior, K.; Tholey, A.; Heisel, S.; Keller, A.; Lenhof, H.-P.; Meese, E.; Huber, C. G. Protein- versus peptide fractionation in the first dimension of two-dimensional high-performance liquid chromatography-matrix-assisted laser desorption/ionization tandem mass spectrometry for qualitative proteome analysis of tissue samples. J. Chromatogr., A 2010, 1217 (40), 6159−6168. (18) Searle, B. C. Scaffold: A bioinformatic tool for validating MS/ MS-based proteomic studies. Proteomics 2010, 10 (6), 1265−1269. (19) Eng, J. K.; Searle, B. C.; Clauser, K. R.; Tabb, D. L., A Face in the Crowd: Recognizing Peptides Through Database Search. Mol. Cell. Proteomics 2011, 10 (11). (20) Dillon, T. M.; Bondarenko, P. V.; Rehder, D. S.; Pipes, G. D.; Kleemann, G. R.; Speed, R. M. Optimization of a reversed-phase highperformance liquid chromatography/mass spectrometry method for characterizing recombinant antibody heterogeneity and stability. J. Chromatogr., A 2006, 1120 (1), 112−120. (21) Wagner, A. Energy Constraints on the Evolution of Gene Expression. Mol. Biol. Evol. 2005, 22 (6), 1365−1374. (22) Fraenkel, D. G. Carbohydrate metabolism [in yeast]. Cold Spring Harbor Monogr. Ser. 1982, 11B, 1−37. (23) Sprague, G. F.; Cronan, J. E. Isolation and characterization of Saccharomyces cerevisiae mutants defective in glycerol catabolism. J. Bacteriol. 1977, 129 (3), 1335−1342. (24) Grauslund, M.; Lopes, J. M.; Rønnow, B. Expression of GUT1, which encodes glycerol kinase in Saccharomyces cerevisiae, is controlled by the positive regulators Adr1p, Ino2p and Ino4p and the negative regulator Opi1p in a carbon source-dependent fashion. Nucleic Acids Res. 1999, 27 (22), 4391−4398. (25) Cronwright, G. R.; Rohwer, J. M.; Prior, B. A. Metabolic Control Analysis of Glycerol Synthesis in Saccharomyces cerevisiae. Appl. Environ. Microbiol. 2002, 68 (9), 4448−4456. (26) ter Schure, E. G.; Flikweert, M. T.; van Dijken, J. P.; Pronk, J. T.; Verrips, C. T. Pyruvate Decarboxylase Catalyzes Decarboxylation of Branched-Chain 2-Oxo Acids but Is Not Essential for Fusel Alcohol Production by Saccharomyces cerevisiae. Appl. Environ. Microbiol. 1998, 64 (4), 1303−1307. (27) Brewster, N. K.; Val, D. L.; Walker, M. E.; Wallace, J. C. Regulation of Pyruvate Carboxylase Isozyme (PYC1, PYC2) Gene Expression in Saccharomyces cerevisiae during Fermentative and Nonfermentative Growth. Arch. Biochem. Biophys. 1994, 311 (1), 62− 71.

(28) Pavlik, P.; Simon, M.; Schuster, T.; Ruis, H. The glycerol kinase (GUT1) gene of Saccharomyces cerevisiae cloning and characterization. Curr. Genet. 1993, 24 (1), 21−25. (29) Blumberg, H.; Hartshorne, T. A.; Young, E. T. Regulation of expression and activity of the yeast transcription factor ADR1. Mol. Cell. Biol. 1988, 8 (5), 1868−1876. (30) Kratzer, S.; Schüller, H.-J. Transcriptional control of the yeast acetyl-CoA synthetase gene, ACS1, by the positive regulators CAT8 and ADR1 and the pleiotropic repressor UME6. Mol. Microbiol. 1997, 26 (4), 631−641. (31) Simon, M.; Binder, M.; Adam, G.; Hartig, A.; Ruis, H. Control of peroxisome proliferation in Saccharomyces cerevisiae by ADR1, SNF1 (CAT1, CCR1) and SNF4 (CAT3). Yeast 1992, 8 (4), 303− 309. (32) Kellis, M.; Patterson, N.; Endrizzi, M.; Birren, B.; Lander, E. S. Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature 2003, 423 (6937), 241−254. (33) Gu, H.; Huang, Y.; Carr, P. W. Peak capacity optimization in comprehensive two dimensional liquid chromatography: A practical approach. J. Chromatogr., A 2011, 1218 (1), 64−73.

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Prefractionation of Intact Proteins by Reversed-Phase and Anion

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