A Protein Processing Filter Method for Bacterial Identification by

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A Protein Processing Filter Method for Bacterial Identification by Mass Spectrometry-Based Proteomics Rabih E. Jabbour,*,† Samir V. Deshpande,‡ Michael F. Stanford,§ Charles H. Wick,§ Alan W. Zulich,§ and A. Peter Snyder§ SAIC, Aberdeen Proving Ground, Maryland 21010, United States, Science and Technology Corporation, Edgewood, Maryland 21040, United States, and U.S. Army Edgewood Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010-5424, United States Received September 18, 2010

Abstract: A “one-pot” alternative method for processing proteins and isolating peptide mixtures from bacterial samples is presented for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and data reduction. The conventional in-solution digestion of the protein contents of bacteria is compared to a small disposable filter unit placed inside a centrifuge vial for processing and digestion of bacterial proteins. Each processing stage allows filtration of excess reactants and unwanted byproduct while retaining the proteins. Upon addition of trypsin, the peptide mixture solution is passed through the filter while retaining the trypsin enzyme. The peptide mixture is then analyzed by LC-MS/MS with an in-house BACid algorithm for a comparison of the experimental unique peptides to a constructed proteome database of bacterial genus, specie, and strain entries. The concentration of bacteria was varied from 10 × 107 to 3.3 × 103 cfu/mL for analysis of the effect of concentration on the ability of the sample processing, LC-MS/MS, and data analysis methods to identify bacteria. The protein processing method and dilution procedure result in reliable identification of pure suspensions and mixtures at high and low bacterial concentrations. Keywords: Protein extraction • proteomics • microbial identification • database search • bacteria • liquid chromatography-mass spectrometry

Introduction Effective sample processing is a critical element for a program that requires the separation and analysis of complex biochemical components from their intact biological host such as bacteria. When only a subset of biochemical entities defines a sample interrogation and interpretation methodology, the challenge lies in producing conditions that yield their greatest efficiency of capture and extraction from the cellular milieu for subsequent delivery into the detector. Efficiency aspects can include the degree and amount of biomolecule analyte extrac* Telephone 410-436-2596. Fax 410-436-1912. E-mail: rabih.jabbour@ us.army.mil. † SAIC, Aberdeen Proving Ground. ‡ Science and Technology Corporation. § U.S. Army Edgewood Chemical Biological Center. 10.1021/pr101086a

 2011 American Chemical Society

tion, complexity of the physical processing conditions and modules, ease of biomolecule subset concentration with interference removal, analyte transfer away from the modules, and ion space-charge consideration in the mass spectrometry ion trap detector. These attributes especially can help in the rapid analysis from first responder, environmental or terrorist, and medical/clinical scenarios where efficient sample handling and sensitivity are of paramount importance in biosafety situations. Processing of microorganism proteins for proteomics analysis over the past decade has developed into three main methods. Initially, all processing methods rely on cellular lysis to provide access to the vast milieu of proteins. Then either online or off-line transfer of the protein-laden supernatant is performed for additional processing. An important method of protein separation that has found extensive utility is twodimensional (2-D) polyacrylamide gel electrophoresis (PAGE).1,2,8 However, processing of the many separated proteins is performed by excising a protein spot from the gel with subsequent purification, concentration, and trypsin digestion. The physical manipulations of the PAGE method are very time consuming, and there are inherent limitations such as not providing for the realization of proteins with low and high molecular weight, low and high pI values, and the capture of nonpolar membrane bound proteins.3,4 Recently, alternative methods have been developed for direct protein processing with liquid and/or stationary supports.3,5-7,9,10 Preprocessing consisted of protein precipitation, denaturation using concentrated urea to remove the protein secondary and tertiary structures, dithiothreitol (DTT) disulfide reduction, and alkylation steps. Trypsin digestion was then performed either in solution or on solid phase porozyme media. The peptide supernatant was concentrated and/or introduced into a system which consisted of a strong cation exchange (SCX)-reversed phase LC-tandem mass spectrometry system (LC-MS/MS) for comprehensive peptide separation and detection. The detailed sequence of steps usually followed different degrees of online status, where some steps were manual and others were performed from one step to the next with sample transfer from one module to the next module. Craft and Li et al.11 integrated a heated cleanup and digestion module for cytochrome c and bovine serum albumin protein standards prior to LC-MS/MS analysis. Ma et al.12 took this a significant step further and combined thermal denaturation, Journal of Proteome Research 2011, 10, 907–912 907 Published on Web 12/02/2010

technical notes reduction, digestion, and peptide preconcentration of protein standards and mouse liver protein extract for LC-MS/MS peptide characterization. In another method, many of the initial procedures were combined into a “one-pot” system. Ethier et al.13 constructed an SCX proteomic reactor to accept the cell lysate. Sequential processing steps took place; however, it was unclear as to the fate of the residual reactants and byproduct in the denaturation, DTT reduction, iodoacetamide (IA) alkylation, and trypsin digestion steps. Evaporation and concentration completed the peptide processing, and the peptides were presented to an LC-MS/MS for separation and analysis. The concern here is that the reagents for each step prior to the LC-MS/MS were not removed or separated, and this was also of concern by Ma et al.12 It was possible that the reduction/alkylation/trypsin digestion reactants and residual products remained in the reactant SCX column to cause potential suboptimal conditions for protein processing. The work reported herein relies on proteome database analyses between bacterial strains and their multiple respective strains resident in a bacterial proteome database. Matrixassisted laser desorption ionization (MALDI)-MS literature also provides ample evidence of proteome studies on bacterial strains for identification purposes. Staphylococcus aureus,14 Escherichia coli,15 Campylobacter,16 Bacillus species17-19 including Bacillus anthracis,20 and Rhodococcus erythropolis21 were investigated for strain differentiation by MALDI-MS. Sample preparation and handling procedures essentially relied on either intact, lysed, or sonicated cells and subsequent mixing with a suitable organic matrix. The purpose of the present work was to seek procedures toward a comprehensive and convenient processing of bacterial cell lysate proteins into a “one-pot” design with no off-line components including the removal of reactants, byproduct, undigested protein, and bacterial debris after each step.22,23 These compounds and components were directed away and upstream from the analytical peptide separation and detection LC-MS/MS system. A 3 kDa molecular weight cutoff (MWCO) membrane was used without LC column or separation components; therefore, the proteins were retained during processing. Once peptides were generated on the 3 kDa MWCO membrane by trypsin digestion, they were passed through the membrane and loaded onto the analytical LC column for mass spectral analysis. The trypsin enzyme was retained by the membrane. In a similar methodology philosophy, Wisniewski et al.24,25 outlined a filter-aided sample preparation (FASP) method detailing a “one-pot” procedure that highlighted the removal of low-molecular weight reagents and impurities while retaining the high-molecular weight species. The retained protein extract was then digested so as to pass through the peptides and retain the trypsin species. Wisniewski et al.24,25 applied their FASP method to bovine serum albumin and HeLa cells. We extend the FASP work to the isolation of a bacterial protein extract and its peptide mixture and that of a mixture of bacteria. Herein, the “one-pot” analysis also was compared with the conventional in-solution digestion method for identification and reproducibility in a range of concentrations for pure bacteria and a mixture of bacteria.

Methods Materials and Reagents. Ammonium bicarbonate (ABC), dithiothreitol (DTT), urea, acetonitrile HPLC grade (ACN), and 908

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Jabbour et al. formic acid (FA) were purchased from Burdick and Jackson Laboratories, Inc. (Muskegon, MI 49442). Sequencing grade modified trypsin was purchased from Promega (Madison, WI), and myoglobin (from equine heart) was purchased from SigmaAldrich (St. Louis, MO 63178). Microbiological Sample Preparations. B. subtilis 168, S. aureus ATCC 12600 and E. coli K-12 preparation and handling procedures can be found elsewhere.26,27 Bacterial Dilution. The ability of the peptide analysis sequencing and data reduction methods to effect bacterial differentiation was tested by varying the concentration of bacteria from 10 × 107 to 10 × 104. The dilution protocol was a standard serial dilution from different vials. Two milliliters of a 2 × 107 cfu/mL stock suspension of bacteria was placed in a separate vial. This 2 mL volume was sonicated for a total of 3 min (Branson Digital Sonifier, Danbury, CT 06810) consisting of 20 s pulse on and 5 s pulse off intervals. A 25% amplitude was chosen in order to lyse the cells. To verify that the cells were disrupted, a small portion of the lysate was reserved for 1-D gel analysis. Five hundred microliters of the sonicated suspension was transferred to another vial, and 500 µL of ABC buffer was added to yield 1 mL of an equivalent 10 × 107 cfu/ mL. One hundred microliters from the sonicated 10 × 107 bacterial suspension was transferred into another vial, and 900 µL of ABC buffer was added to yield 1 mL of an equivalent 10 × 106 cfu/mL suspension of bacteria. Two more iterations were performed to produce 10 × 105 and 10 × 104 cfu/mL equivalent suspensions of bacteria. Note that all four dilutions resulted from one stock sonicated bacterial suspension. For all four dilutions, each was performed three times to yield a standard deviation for each replicate series. The dilution method was investigated for its impact on the ability to define the sample bacterium from a proteomics statistical analysis. Bacterial Mixture Analysis. An experiment was conducted where equal volumes of 10 × 107 cfu/mL suspensions of E. coli K-12, S. aureus 12600, and B. subtilis 168 were added into a vial to result in a 3.3 × 106 cfu/mL for each bacterium. This experiment was conducted in a double blind situation.26 The mixture was sonicated for 3 min to release the cellular proteins for further processing. The dilution series protocol was conducted to test the ability of the procedures and data analysis methods to detect and define the number and identity of organisms present in the mixture at different concentrations. Bacterial Processing. Two methods were used to isolate and digest the protein portion of the bacteria. The first method was basically the in-solution digestion technique13 with some modifications. One milliliter of a given dilution and lysed bacterial suspension was placed into vial 1 (V1). V1 was centrifuged for 10 min at 14,000 rpm. The protein laden supernatant was pipetted into a Microcon YM-10 filter unit (Millipore #42406) with a 10,000 Da molecular weight cutoff, and the filter unit was inserted into V2. Vial V2 was centrifuged to remove the liquid. The proteins were retained on the filter surface and the filtrate was discarded. Fifty microliters of 100 mM ABC buffer was added to dissolve the proteins, and the liquid was retained on the filter. The filter unit was inserted into V2 and vortexed. The filter unit was then turned upside down in V3 and the assembly was centrifuged to deposit the approximately 50 µL protein laden liquid onto the bottom of V3. Thirty microliters of DTT (10 µg/mL) and 270 µL of 8 M urea was added into V3 and placed in a 45 °C oven for one hour to denature the protein. One milliliter of ABC buffer was added to V3 and evaporated in a SpeedVac. Then 5 µL of trypsin

Solution-Digestion Filter Method to Identify Bacteria (1 mg/mL), 20 µL of ABC buffer, and 5 µL of ACN were added and vortexed briefly to dissolve the protein on the inside walls of V3. Protein digestion occurred overnight at 37 °C on an orbital shaker at 55 rpm. Sixty microliters of 5% ACN/0.5% FA was added with 2 min of vortexing for sample mixing to quench the digestion. The liquid was evaporated in a SpeedVac. The peptides were reconstituted with 100 µL of LC buffer (vide infra). Ten microliters of the peptide solution was injected into the LC column. The solution-digestion filter method was the alternative set of procedures used for bacterial protein isolation and digestion.22,23 This method begins with the in-solution digestion method and instead of turning the filter upside down, the filter remained right side up in V2. Fifty microliters of ABC buffer was added onto the filter and centrifuged to effect a buffer exchange. The proteins were retained on the filter. DTT and urea were added onto the filter, and the V2-filter assembly was placed in a 45 °C oven for one hour. One hundred microliters of ABC buffer was added to dilute the urea, and V2 was centrifuged. Another 100 µL of ABC buffer application was performed, and V2 was centrifuged. Trypsin was then added with the ABC/ACN solution as in method A. Protein digestion occurred overnight in a 37 °C oven on an orbital shaker at 55 rpm. Sixty microliters of 5% ACN/0.5% FA was added with 2 min of vortexing to quench the digestion. V2 was replaced with V3, and the unit was centrifuged to collect the peptide supernatant. Ten microliters of the supernatant was injected into the LC column. LC-MS/MS Analysis and Protein Database. These procedures are outlined elsewhere.22,23

Results and Discussion An objective of this work was to reduce the number of surfaces and vials necessary to process bacteria into an isolated protein extract and peptide mixture when compared to the standard in-solution digestion technique. This modified, somewhat streamlined procedure is labeled the solution-digestion filter method. A proteome-based identification of the mass spectral peptide response would provide an adequate measure of the efficacy of the solution-digestion filter method. Different concentrations of a protein mixture extract from the same bacterium can yield different qualitative and quantitative information. This can affect performance of the proteome data analysis algorithms, and as such, bacterial concentrations ranged from 10 × 107 to 10 × 104 cfu/mL. Myoglobin Peptide Recovery Efficiency. Pure myoglobin protein was subjected to the two different processing methods. Figure 1a presents an LC chromatogram of the myoglobin peptide mixture after processing with the standard in-solution digestion method. Note in particular the circled, broad peak around 90 min. The separation procedure shows that the reagents and buffer components are subjected to lyophilization in the processing steps. However, a portion of the reagents such as DTT, urea, FA, ACN buffer, and undigested myoglobin may be present in a residual capacity in the peptide-laden sample injected into the LC system. This appears to affect the qualitative and quantitative recovery of the peptides as shown in Figure 1b, and each procedure was performed in three replicate measurements. Figure 1b presents the LC chromatogram of the myoglobin peptide mixture from the solution-digestion filter method. The ordinate scale was normalized for comparison purposes for Figures 1a, b. Over twice as much peptide recovery was realized with respect to relative abundance (ordinate scale

technical notes

Figure 1. Liquid chromatography mass spectral chromatograms of peptides from a trypsin digest of myoglobin using the (a) standard in-solution digestion and (b) solution-digestion filter methods. The intensities are scaled relative to the chromatogram in (b).

information) when the residual reagents and byproduct were eliminated. These materials are not observed about the 90 min time frame in Figure 1b. Also, a peak at 68-69 min is prominently observed in Figure 1b while it is virtually absent in Figure 1a. More peptides (Table S1, Supporting Information) are retained with >95% probability with the filter method (10 peptides) compared to the in-solution digestion method (7 peptides). This may be partially due to fewer manipulations associated with the procedures in the filter processing steps. Table S1 (Supporting Information) provides details of the recovered peptides with a greater than or equal to 95% PeptideProphet probability for both protein processing methods, and the Xcorr values also are given.28 There are three myoglobin misclassified peptides in the filter processing method, and one of them (K.YKELGFQG) is observed from the in-solution digestion procedure. The two additional misclassified peptides are not a function of the procedural steps. Rather, they are a product of the trypsin digestion which is a common component for both processing methods. Therefore, this is evidence for the in-solution digestion method having a role in prevention, retardation, or inhibition of the admittance into the LC of the K.ALELFRNDIAAK.Y and K.GHHEAELKPLAQSHATK.H peptides. This interpretation is also likely for the three other unique peptides (Table S1, Supporting Information) observed from the filter processing method as well as the two unique peptides observed from the standard in-solution digestion method. Bacterial Peptide Recovery. Only the solution-digestion filter method is utilized for the remainder of the experiments, because it outperformed the standard method. Figure 2 compares the number of unique peptides using the bacterial dilution protocol with the solution-digestion filter processing method. Separate suspensions of a Gram-negative and two Gram-positive organisms were used for the dilution comparisons. For each concentration and each organism, three separate experiments were performed. The average is plotted for each bacterial concentration with standard deviation error bars. As expected, as the amount of lysed bacterial protein preparation Journal of Proteome Research • Vol. 10, No. 2, 2011 909

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Figure 2. Number of unique peptides possessing >95% probability score from PeptideProphet using two sample dilution protocols (see text). The solution-digestion filter processing method was used to isolate the peptides for all three bacteria at concentrations of 3.3 × 106, 3.3 × 105, 3.3 ×104, and 3.3 × 103 cfu/mL. The abscissa reflects the total concentration of the experimental bacterial mixture.

decreased, fewer peptides were observed. The concentration of protein in a bacterial cell varies by many decades depending on the specific protein. Therefore, in one sense, the proteins with a relatively high concentration usually have a greater probability of detection from their peptide digestion products compared to the proteins with a smaller concentration. However, in an opposite effect, the higher concentration sample will have a greater likelihood for an elution of peptides exhibiting a higher number and amount per unit time through the LC column. In this situation, the relatively lower concentration of certain peptides in a particular LC elution time may be masked by the peptide(s) that exhibit a higher concentration. This can be manifested in the spectra through competition of proton charge. Overall proton affinities also play a role in the percent of charge acquisition that a particular peptide has with co-eluting peptide(s) at a certain LC column retention time. There is a dilution effect, and the trend is in the same direction for both organisms. Furthermore, the space-charge effects in the limited ion trap volume may also favor more abundant peptides. Ion trap space-charge effects can indiscriminately remove a percentage of peptides eluting from the LC. The higher abundant peptides will most likely be favored in the ion trap fill volume than the lower abundant peptides. This space charge removal of peptides may cause a greater loss for the less abundant peptides and possibly render less abundant bacterial discriminating peptides undetectable. The trends in Figure 2 display an overall decrease in the appearance of peptides with decreasing protein extract concentration, and this may affect the outcome of a detection and identification analysis (vide infra). Spores have a greatly reduced need, compared to a typical vegetative bacterial cell, to produce a full complement of proteins in a ready-to-use state for cellular functions. The dormant state of a spore precludes the necessity for the actual presence of many cell function and housekeeping proteins. Thus, it is no surprise to observe the significant decrease in number of peptides for B. subtilis spores compared to those for S. aureus and E. coli in Figure 2. To the best of the authors’ 910

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Jabbour et al. knowledge, analyses of the number of unique peptides derived from single and mixtures of whole bacteria suspensions at different concentrations have not been related in the literature. Bacterial Mixture Peptide Recovery. A mixture of three bacteria was prepared with equal volumes of equimolar bacterial stock suspensions. This was a double blind sample, and we were unaware of the identity and number of organisms in the mixture. We were informed that the total bacterial concentration was approximately 10 × 107 cfu/mL. One milliliter of the 2 mL double blind mixture suspension was used for identification and dilution studies. Each dilution was separately sonicated and lysed for 3 min. The histogram in Figure S1 (Supporting Information) presents the results where the peptide mixtures were analyzed and separated into three bacterial species using the BACid program and further delineated into strains. Plots are represented as the number of unique peptides for each of E. coli, S. aureus, and B. subtilis that were identified and subsequently confirmed following the data reduction procedures for bacterial identification found elsewhere.26,29 Subsequently, we were told that the double blind suspension was prepared by adding equal volumes together of equal concentrations of the three organisms. Once the identities and number of bacteria in the mixture were confirmed, this information shaped the standard dilution series in Figure 2. The general trend of a decreasing number of unique peptides, resulting from statistical analysis of the product ion mass spectra, is observed with a decrease in protein extract concentration. An interesting observation is that the peptide trends for all three organisms do not show a “flat-lining” or horizontal trend at the experimental concentrations used. Rather, a decreasing trend is sustained below 10 × 104 cfu/mL. Thus, there are unique peptides even at the relatively low 3.33 × 103 cfu/mL bacterial equivalent protein extract concentration. The correct identity26 was determined for each of the three bacteria at all four suspension dilutions. Bacterial Classification Analysis. Using the solution-digestion filter method, analyses were performed with known and double blind bacterial suspensions at different concentrations. Lower concentrations of bacteria in general provided a lower amount of peptide recovery. Lower bacterial concentrations of 3.3 × 103 and 3.3 × 104 organisms provided satisfactory identification capabilities (Figures 2 and S1). Figure S2 [SI] and Figure 3 provide dendrogram details of the concentration effect on the qualitative and quantitative aspects of the unique peptide parameters. A level of confidence analysis was performed for the dendrogram results. Three separate bacterial suspensions were prepared and analyzed, and Figures S2a, b [SI] and Figures 3a, b present consistent examples of the replicate analyses. Figure S2a (Supporting Information) presents a known E. coli study where the concentration was 10 × 106 cfu/mL. Following the rules of the shortest single linkage Euclidean distance approach as outlined in the literature,30,31 the E. coli K-12 strain (labeled ‘Sample’ in Figure S2a (SI)) provides the shortest distance to the database E. coli K-12 entry. The number of unique peptides isolated was 372. In Figure S2b (SI), the known E. coli K-12 concentration was 10 × 104 cfu/ mL. At this lower concentration, enough unique peptides (204) were captured by the sample processing, LC-MS/MS, and BACid analysis to identify the sample as E. coli K-12. Figure 3a provides a classification result from a double blind study of a dendrogram analysis using the single linkage Euclidean distance method. The concentration of the bacterial

technical notes

Solution-Digestion Filter Method to Identify Bacteria

Figure 3. Dendrograms of double blind suspensions later revealed to be S. aureus ATCC 12600. The solution-digestion filter processing and the single linkage Euclidean distance data analysis statistical methods were used. (a) Given concentration of 10 × 107 cfu/mL and (b) 10 × 104 cfu/mL arrived at by serial dilution.

suspension was given at 10 × 107 cfu/mL; however, we were not given that information until after our results were reported. Serial dilutions were prepared in decades to a 10 × 104 cfu/ mL suspension. The bacterial strain data reduction and analysis resulted in 425 unique peptides for one bacterium. The double blind sample was closest to pathogenic S. aureus RF122 at a relatively high concentration of 10 × 107 cfu/mL. At a lower concentration (Figure 3b), pathogenic S. aureus MRSA252 and S. aureus RF122 were determined to be the closest strains to the sample strain with 198 unique peptides. The bacterium was subsequently revealed to be the pathogenic S. aureus ATCC 12600 organism. This particular strain is not contained in the database, because its genome has not been sequenced. The reason a nondatabase organism was investigated was to determine if the processing and data reduction methods would “force” a definitive, albeit wrong, result from among the database entries. The analysis did not produce a database organism response; rather, it identified the experimental sample within the group of S. aureus strains.

Conclusion When confronted with multiple processing and concentration steps, confining a complex protein mixture in one container provides quantitative and qualitative benefits. The relative protein signals increase in intensity compared to those in the standard in-solution digestion technique partly because the transfers of the protein mixture to different vials produce sample loss. Furthermore, the filter nature of the vial allowed the low-molecular weight reactants and byproduct to be separated from the processed proteins so as not to interfere with subsequent processing steps. The resulting peptide mixture was easily separated from the trypsin cleavage enzyme. The quantity of peptides and their percent of protein coverage both approximately are doubled, with respect to abundance, from the in-solution digestion method compared to the solution-digestion filter technique introduced herein. Pure suspensions and mixtures of organisms were amenable to the filter processing method for the capture of the protein Journal of Proteome Research • Vol. 10, No. 2, 2011 911

technical notes content and processing them into peptides. The concentrated to relatively dilute bacterial suspensions were amenable to the protein and peptide isolation techniques with respect to the identification of the sample. The qualitative and quantitative characteristics of efficient protein extraction were shown by the solution-digestion filter processing method for facilitation in the identification of bacterial samples including mixtures.

Acknowledgment. We thank Dr. Ilya Elashvili at the Defense Threat Reduction Agency (DTRA) for funding the research presented herein. Supporting Information Available: This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Lambert, J.-P.; Ethier, M.; Smith, J. C.; Figys, D. Anal. Chem. 2005, 77, 3771–3788. (2) Quadroni, M.; James, P. Electrophoresis 1999, 20, 664–677. (3) Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242–247. (4) Ihling, C.; Sinz, A. Proteomics 2005, 5, 2029–2042. (5) Vollmer, M.; Nagele, E.; Horth, P. J. Biomol. Tech. 2003, 14, 128– 135. (6) Salzano, A. M.; Arena, S.; Renzone, G.; D’Ambrosio, C.; Rullo, R.; Bruschi, M.; Ledda, L.; Maglione, G.; Candiano, G.; Ferrara, L.; Scaloni, A. Proteomics 2007, 7, 1420–1433. (7) Malen, H.; Berven, F. S.; Softeland, T.; Arntzen, M. O.; D’Santos, C. S.; De Souza, G. A.; Wiker, H. G. Proteomics 2008, 8, 1859–1870. (8) Lopez, M. F. Electrophoresis 2000, 21, 1082–1093. (9) Dai, J.; Shieh, C. H.; Sheng, Q.-H.; Zhou, H.; Zeng, R. Anal. Chem. 2005, 77, 5793–5799. (10) Wu, C. C.; MacCoss, M. J.; Howell, K. E.; Yates, J. R., III. Nat. Biotechnol. 2003, 21, 532–538. (11) Craft, D.; Li, L. Anal. Chem. 2005, 77, 2649–2655. (12) Ma, J.; Liu, J.; Sun, L.; Gao, L.; Liang, Z.; Zhang, L.; Zhang, Y. Anal. Chem. 2009, 81, 6534–6540. (13) Ethier, F.; Hou, W.; Duewel, H. S.; Figeys, D. J. Proteome Res. 2006, 5, 2754–2759. (14) Walker, J.; Fox, A. J.; Edwards-Jones, V.; Gordon, D. B. J. Microbiol. Methods 2002, 48, 117–126. (15) Bright, J. J.; Claydon, M. A.; Soufian, M.; Gordon, D. B. J. Microbiol. Methods 2002, 48, 127–138.

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