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and Fenyo¨ analyzed the error introduced at each step, then used this information to design a workflow and predict the overall error. The first step was IP. Proteins from light and heavy SILAC samples were immunoprecipitated separately, then mixed and analyzed by 1DE and LC/ MS/MS; this experiment was called N ) 1. To assess the effect of replicates
Surprisingly, the random error inherent in two popular sample preparation methods is low, according to researchers at the New York University School of Medicine and Rockefeller University. As Thomas Neubert, Guoan Zhang, and David Fenyo¨ report in JPR (DOI 10.1021/pr8006107), immunoprecipitation (IP) and in-gel digestion, which are often included in quantitative proteomics workflows, can be highly reproducible. Proteomics researchers have a lot of choices when deciding on a relative quantitation method. With some methods, scientists label and mix peptides from different samples after most sample preparation procedures have been performed. With stable-isotope labeling by amino acids in cell culture (SILAC), however, cells are grown on isotopically labeled media, and label is incorporated into the proteins as they are synthesized. Neubert considers SILAC to be one of the most accurate quantitation methods. “The samples that are being compared are in the same test tube, Preparing for error. Schematic of the workflow used to evaluate the error introduced by two popular sample so they’re treated exactly the preparation methods. same way during sample preparation,” he explains. But SILAC can be applied only to cell lines and some model organon the protocol, the researchers also isms. In addition, the method requires conducted an N ) 3 experiment in the purchase of special amino acids. which three separate sets of heavy IPs So, to analyze human tissues or large and three sets of light IPs were pernumbers of samples, researchers often formed independently; then all the perform label-free quantitation. Howsamples were mixed and analyzed by ever, because these samples are never 1DE and LC/MS/MS. Likewise, an N ) mixed during preparation, varying de6 experiment was performed. Finally, grees of random error can be introas a control, light and heavy samples duced to individual samples at any were mixed before IP. The N ) 1, 3, 6, step; this error can skew the results. and control procedures were carried “Before we can do [label-free methout three times. ods], we need to know how much error Because the light and heavy samples is introduced in sample preparation,” were treated in the same way before says Neubert. But few scientists have lysis, the researchers expected a 1:1 investigated sample preparation error. ratio for all proteins. Also, the control “It’s probably not glamorous, but I samples were mixed immediately after think it’s absolutely essential,” he adds. lysis, so sample preparation should not To evaluate the typical variation inhave affected this part of the experitroduced during a quantitative proment. According to the statistical teomics experiment, Neubert, Zhang,
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Journal of Proteome Research • Vol. 8, No. 3, 2009
analysis, the N ) 1 ratios were the most variable. The N ) 3 and N ) 6 ratios were almost identical to each other and to the control, so three replicates appear to be ideal for IP. A similar set of experiments was performed to evaluate the error introduced during in-gel digestion of proteins in excised 1DE gel bands. A technical problem almost derailed the assessment, however. Neubert explains, “If you have separation of proteins, it’s very difficult to cut out a gel band that contains the exact same set of proteins,” even if the same sample is run in two lanes side by side. “Guoan got around thatsthis is a clever ideasby adding the lysate to the gel before it was polymerized,” notes Neubert. The proteins were mixed into the acrylamide solution, so that once the polymerizing agent was added, the proteins were evenly distributed. All gel slices contained the same proteins. Proteins within the gel slices were in-gel digested in an N ) 1, 3, or 6 experiment, then mixed and analyzed by LC/MS/MS. Virtually no differences were observed among the ratios obtained for the three types of experiments. Thus, only one replicate is necessary for in-gel digestion. With the information from these two sets of experiments in hand (in addition to variability data on 1DE gels calculated from previous work), the team predicted the expected error and optimal number of replicates for a quantitative proteomics workflow comprising IP, 1DE, in-gel digestion, and LC/MS/MS. Then, the entire workflow was performed. The theoretical error matched the experimental error closely. Although researchers may be tempted to run out and perform the same number of replicates and expect to obtain the same variability, Neubert cautions that these errors may be operator-dependent. “I think that different individuals would probably have different-looking curves,” he states. “But by looking at these [data], you know that at least this kind of reproducibility can be achieved.” —Katie Cottingham THOMAS NEUBERT
Variability is low in some sample preparation methods
10.1021/pr801101x
© 2009 American Chemical Society
