The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics.
ABSTRACT: The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.
Project description:For data-independent acquisition by means of sequential window acquisition of all theoretical fragment ion spectra (SWATH), a reference library of data-dependent acquisition (DDA) runs is typically used to correlate the quantitative data from the fragment ion spectra with peptide identifications. The quality and coverage of such a reference library is therefore essential when processing SWATH data. In general, library sizes can be increased by reducing the impact of DDA precursor selection with replicate runs or fractionation. However, these strategies can affect the match between the library and SWATH measurement, and thus larger library sizes do not necessarily correspond to improved SWATH quantification. Here, three fractionation strategies to increase local library size were compared to standard library building using replicate DDA injection: protein SDS-PAGE fractionation, peptide high-pH RP-HPLC fractionation and MS-acquisition gas phase fractionation. The impact of these libraries on SWATH performance was evaluated in terms of the number of extracted peptides and proteins, the match quality of the peptides and the extraction reproducibility of the transitions. These analyses were conducted using the hydrophilic proteome of differentiating human embryonic stem cells. Our results show that SWATH quantitative results and interpretations are affected by choice of fractionation technique. Data are available via ProteomeXchange with identifier PXD006190.
Project description:Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.
Project description:State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.
Project description:For historical reasons, most proteomics workflows focus on MS/MS identification but consider quantification as the end point of a comparative study. The stochastic data-dependent MS/MS acquisition (DDA) gives low reproducibility of peptide identifications from one run to another, which inevitably results in problems with missing values when quantifying the same peptide across a series of label-free experiments. However, the signal from the molecular ion is almost always present among the MS(1)spectra. Contrary to what is frequently claimed, missing values do not have to be an intrinsic problem of DDA approaches that perform quantification at the MS(1)level. The challenge is to perform sound peptide identity propagation across multiple high-resolution LC-MS/MS experiments, from runs with MS/MS-based identifications to runs where such information is absent. Here, we present a new analytical workflow DeMix-Q (https://github.com/userbz/DeMix-Q), which performs such propagation that recovers missing values reliably by using a novel scoring scheme for quality control. Compared with traditional workflows for DDA as well as previous DIA studies, DeMix-Q achieves deeper proteome coverage, fewer missing values, and lower quantification variance on a benchmark dataset. This quantification-centered workflow also enables flexible and robust proteome characterization based on covariation of peptide abundances.
Project description:Receptor for Activated protein C kinase 1 (RACK1) is a scaffold protein that has been found in association with several signaling complexes, and with the 40S subunit of the ribosome. Using the model organism Drosophila melanogaster, we recently showed that RACK1 is required at the ribosome for internal ribosome entry site (IRES)-mediated translation of viruses. Here, we report a proteomic characterization of the interactome of RACK1 in Drosophila S2 cells. We carried out Label-Free quantitation using both Data-Dependent and Data-Independent Acquisition (DDA and DIA, respectively) and observed a significant advantage for the Sequential Window Acquisition of all THeoretical fragment-ion spectra (SWATH) method, both in terms of identification of interactants and quantification of low abundance proteins. These data represent the first SWATH spectral library available for Drosophila and will be a useful resource for the community. A total of 52 interacting proteins were identified, including several molecules involved in translation such as structural components of the ribosome, factors regulating translation initiation or elongation, and RNA binding proteins. Among these 52 proteins, 15 were identified as partners by the SWATH strategy only. Interestingly, these 15 proteins are significantly enriched for the functions translation and nucleic acid binding. This enrichment reflects the engagement of RACK1 at the ribosome and highlights the added value of SWATH analysis. A functional screen did not reveal any protein sharing the interesting properties of RACK1, which is required for IRES-dependent translation and not essential for cell viability. Intriguingly however, 10 of the RACK1 partners identified restrict replication of Cricket paralysis virus (CrPV), an IRES-containing virus.
Project description:Advances in liquid chromatography-mass spectrometry have facilitated the incorporation of proteomic studies to many biology experimental workflows. Data-independent acquisition platforms, such as sequential window acquisition of all theoretical mass spectra (SWATH-MS), offer several advantages for label-free quantitative assessment of complex proteomes over data-dependent acquisition (DDA) approaches. However, SWATH data interpretation requires spectral libraries as a detailed reference resource. The guinea pig (Cavia porcellus) is an excellent experimental model for translation to many aspects of human physiology and disease, yet there is limited experimental information regarding its proteome. To overcome this knowledge gap, a comprehensive spectral library of the guinea pig proteome is generated. Homogenates and tryptic digests are prepared from 16 tissues and subjected to >200 DDA runs. Analysis of >250 000 peptide-spectrum matches resulted in a library of 73 594 peptides from 7666 proteins. Library validation is provided by i) analyzing externally derived SWATH files (https://doi.org/10.1016/j.jprot.2018.03.023) and comparing peptide intensity quantifications; ii) merging of externally derived data to the base library. This furnishes the research community with a comprehensive proteomic resource that will facilitate future molecular-phenotypic studies using (re-engaging) the guinea pig as an experimental model of relevance to human biology. The spectral library and raw data are freely accessible in the MassIVE repository (MSV000083199).
Project description:Proteomics is often hindered by the lack of protein sequence database particularly for non-model species such as Persicaria minor herbs. An integrative approach called proteomics informed by transcriptomics is possible , in which translated transcriptome sequence database is used as the protein sequence database. In this current study, the proteome profile were profiled using SWATH-MS technology complemented with documented transcriptome profiling , the first such report in this tropical herb. The plant was also elicited using a phytohormone, methyl jasmonate (MeJA) and protein changes were elucidated using label-free quantification of SWATH-MS to understand the role of such signal molecule in this herbal species. The mass spectrometry proteomics data was deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD005749. This data article refers to the article entitled "Proteomics (SWATH-MS)-informed by transcriptomics approach of Persicaria minor leaves upon methyl jasmonate elicitation" .
Project description:Proteomic analysis of extracellular matrix (ECM) and ECM-associated proteins, collectively known as the matrisome, is a challenging task due to the inherent complexity and insolubility of these proteins. Here we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins in both non-enriched and ECM enriched tissue without the need for prior fractionation. Utilising a spectral library containing 201 matrisomal proteins, we compared the performance and reproducibility of SWATH MS over conventional data-dependent analysis mass spectrometry (DDA MS) in unfractionated murine lung and liver. SWATH MS conferred a 15-20% increase in reproducible peptide identification across replicate experiments in both tissue types and identified 54% more matrisomal proteins in the liver versus DDA MS. We further use SWATH MS to evaluate the quantitative changes in matrisome content that accompanies ECM enrichment. Our data shows that ECM enrichment led to a systematic increase in core matrisomal proteins but resulted in significant losses in matrisome-associated proteins including the cathepsins and proteins of the S100 family. Our proof-of-principle study demonstrates the utility of SWATH MS as a versatile tool for in-depth characterisation of the matrisome in unfractionated and non-enriched tissues. SIGNIFICANCE: The matrisome is a complex network of extracellular matrix (ECM) and ECM-associated proteins that provides scaffolding function to tissues and plays important roles in the regulation of fundamental cellular processes. However, due to its inherent complexity and insolubility, proteomic studies of the matrisome typically require the application of enrichment workflows prior to MS analysis. Such enrichment strategies often lead to losses in soluble matrisome-associated components. In this study, we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins. We show that SWATH MS provides a more reproducible coverage of the matrisome compared to data-dependent analysis (DDA) MS. We also demonstrate that SWATH MS is capable of accurate quantification of matrisomal proteins without prior ECM enrichment and fractionation, which may simplify sample handling workflows and avoid losses in matrisome-associated proteins commonly linked to ECM enrichment.
Project description:Bottom-up proteomic strategies rely on efficient digestion of proteins into peptides for mass spectrometry analysis. In-solution and filter-based strategies are commonly used for proteomic analysis. In recent years, filter-aided sample preparation (FASP) has become the dominant filter-based method due to its ability to remove SDS prior to mass spectrometry analysis. However, the time-consuming nature of FASP protocols have led to the development of new filter-based strategies. Suspension traps (S-Traps) were recently reported as an alternative to FASP and in-solution strategies as they allow for high concentrations of SDS in a fraction of the time of a typical FASP protocol. In this study, we compare the yields from in-solution, FASP, and S-Trap based digestions of proteins extracted in SDS and urea-based lysis buffers. We performed label-free quantification to analyze the differences in the portions of the proteome identified using each method. Overall, our results show that each digestion method had a high degree of reproducibility within the method type. However, S-Traps outperformed FASP and in-solution digestions by providing the most efficient digestion with the greatest number of unique protein identifications. This is the first work to provide a direct quantitative comparison of two filter-based digestion methods and a traditional in-solution approach to provide information regarding the most efficient proteomic preparation.
Project description:Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) has emerged as one of the most popular techniques for label-free proteome quantification in current pharmacoproteomic research. It provides more comprehensive detection and more accurate quantitation of proteins comparing with the traditional techniques. The performance of SWATH-MS is highly susceptible to the selection of processing method. Till now, ?27 methods (transformation, normalization, and missing-value imputation) are sequentially applied to construct numerous analysis chains for SWATH-MS, but it is still not clear which analysis chain gives the optimal quantification performance. Herein, the performances of 560 analysis chains for quantifying pharmacoproteomic data were comprehensively assessed. Firstly, the most complete set of the publicly available SWATH-MS based pharmacoproteomic data were collected by comprehensive literature review. Secondly, substantial variations among the performances of various analysis chains were observed, and the consistently well-performed analysis chains (CWPACs) across various datasets were for the first time generalized. Finally, the log and power transformations sequentially followed by the total ion current normalization were discovered as one of the best performed analysis chains for the quantification of SWATH-MS based pharmacoproteomic data. In sum, the CWPACs identified here provided important guidance to the quantification of proteomic data and could therefore facilitate the cutting-edge research in any pharmacoproteomic studies requiring SWATH-MS technique.