Handler, D. C. L. | bioRxiv Science

bioRxiv2020

Comparison of protein and peptide fractionation approaches in protein identification and quantification from Saccharomyces cerevisiae

Proteomics, as a high-throughput technology, has been developed with the aim of investigating the maximum number of proteins in cells. However, protein discovery and data generation vary in depth and coverage when different technical strategies are used. In this study, four different sample preparation, and peptide or protein fractionation, methods were applied to identify and quantify proteins from log-phase yeast lysate: sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE); gas phase fractionation (GPF); filter-aided sample preparation (FASP)- GPF; and FASP-high pH reversed phase fractionation (HpH). Fractionated samples were initially analyzed and compared using nanoflow liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing data dependent acquisition on a linear ion trap instrument. The number of fractions and replicates was adjusted so that each experiment used a similar amount of mass spectrometric instrument time, approximately 16 hours. A second set of experiments was performed using a Q Exactive Orbitrap instrument, comparing FASP-GPF, SDS-PAGE and FASP-HpH. Compared with results from the linear ion trap mass spectrometer, the use of a Q Exactive Orbitrap mass spectrometer enabled a small increase in protein identifications using SDS-PAGE and FASP-GPF methods, and a large increase using FASP-HpH. A big advantage of using the higher resolution instrument found in this study was the substantially increased peptide identifications which enhance the proteome coverage. A total of 1035, 1357 and 2134 proteins were separately identified by FASP-GPF, SDS-PAGE and FASP-HpH. Combining results from the Orbitrap experiments, there were a total of 2269 proteins found, with 94% of them identified using the FASP-HpH method. Therefore, the FASP-HpH method is the optimal choice among these approaches when using a high resolution spectrometer, when applied to this type of sample.

biochemistry↗

bioRxiv2019

An experimentally-derived measure of inter-replicate variation in reference samples: the same-same permutation methodology

The multiple testing problem is a well-known statistical stumbling block in high-throughput data analysis, where large scale repetition of statistical methods introduces unwanted noise into the results. While approaches exist to overcome the multiple testing problem, these methods focus on theoretical statistical clarification rather than incorporating experimentally-derived measures to ensure appropriately tailored analysis parameters. Here, we introduce a method for estimating inter-replicate variability in reference samples for a quantitative proteomics experiment using permutation analysis. This can function as a modulator to multiple testing corrections such as the Benjamini-Hochberg ordered Q value test. We refer to this as a same-same analysis, since this method incorporates the use of six biological replicates of the reference sample and determines, through non-redundant triplet pairwise comparisons, the level of quantitative noise inherent within the system. The method can be used to produce an experiment-specific Q value cut-off that achieves a specified false discovery rate at the quantitation level, such as 1%. The same-same method is applicable to any experimental set that incorporates six replicates of a reference sample. To facilitate access to this approach, we have developed a same-same analysis R module that is freely available and ready to use via the internet.

biochemistry↗