Evaluation and Refinement of Sample Preparation Methods for Extracellular Matrix Proteome Coverage.
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ABSTRACT:
SUBMITTER: McCabe MC
PROVIDER: S-EPMC8188056 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A major challenge in the field of proteomics is obtaining high-quality peptides for comprehensive proteome profiling by LC-MS. Here, evaluation and modification of a range of sample preparation methods using photosynthetically active Arabidopsis leaf tissue are done. It was found that inclusion of filter-aided sample preparation (FASP) based on filter digestion improves all protein extraction methods tested. Ultimately, a detergent-free urea-FASP approach that enables deep and robust quantification of leaf and root proteomes is shown. For example, from 4-day-old leaf tissue, up to 11 690 proteins were profiled from a single sample replicate. This method should be broadly applicable to researchers working with difficult to process plant samples.
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Project description:The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.
| S-EPMC6197446 | biostudies-literature
Project description:The so-called tube-gel method is a sample preparation protocol allowing for management of SDS for protein solubilization through in-gel protein trapping. Because of its simplicity, we assumed that once miniaturized, this method could become a standard for large scale experiments. We evaluated the performances of two variants of the miniaturized version of the tube-gel method based on different solubilization buffers (Tris-SDS or urea-SDS). To this end, we compared them to two other digestion methods: (i) liquid digestion after protein solubilization in the absence of SDS (liquid method) and (ii) filter-aided sample preparation (FASP). As large-scale experiments may require long term gel storage, we also examined to which extent gel aging affected the results of the proteomics analysis. We showed that both tube-gel and FASP methods extracted membrane proteins better than the liquid method, while the latter allowed the identification and quantification of a greater number of proteins. All methods were equivalent regarding quantitative stability. However, important differences were observed regarding post-translational modifications. In particular, methionine oxidation was higher with the tube-gel method than with the other methods. Based on these results, and considering time, simplicity, and cost aspects, we conclude that the miniaturized tube-gel method is suitable for sample preparation in the context of large-scale experiments.
| S-EPMC5874765 | biostudies-literature
Project description:In the past two decades, metabolomics has proved to be a valuable tool with many potential applications in different areas of science. However, there are still some challenges that need to be addressed, particularly for multicenter studies. These challenges are mainly attributed to various sources of fluctuation and unwanted variations that can be introduced at pre-analytical, analytical, and/or post-analytical steps of any metabolomics experiment. Thus, this study aimed at using Streptomyces lividans TK24 as the model organism in a cross-laboratory experiment in Manchester and Leuven to evaluate the reproducibility of a standard sample preparation method, and determine the optimal sample format (cell extract or quenched biomass) required to preserve the metabolic profile of the cells during cross-lab sample transportation and storage. Principal component analysis (PCA) scores plot of the gas chromatography-mass spectrometry (GC-MS) data from both laboratories displayed clear growth-dependent clustering patterns which was in agreement with the Procrustes analysis findings. In addition, the data generated in Manchester displayed tight clustering of cell pellets (quenched biomass) and metabolite extracts, confirming the stability of both sample formats during the transportation and storage period.
| S-EPMC7569812 | biostudies-literature
Project description:Tandem mass spectrometry-based proteotyping allows characterizing microorganisms in terms of taxonomy and is becoming an important tool for investigating microbial diversity from several ecosystems. Fast and automatable sample preparation for obtaining peptide pools amenable to tandem mass spectrometry is necessary for enabling proteotyping as a high-throughput method. First, the protocol to increase the yield of lysis of several representative bacterial and eukaryotic microorganisms was optimized by using a long and drastic bead-beating setting with 0.1 mm silica beads, 0.1 and 0.5 mm glass beads, in presence of detergents. Then, three different methods to obtain greater digestion yield from these extracts were tested and optimized for improve efficiency and reduce application time: denaturing electrophoresis of proteins and in-gel proteolysis, suspension-trapping filter-based approach (S-Trap) and, solid-phase-enhanced sample preparation named SP3. The latter method outperforms the other two in terms of speed and delivers also more peptides and proteins than with the in-gel proteolysis (2.2 fold for both) and S-trap approaches (1.3 and 1.2 fold, respectively). Thus, SP3 directly improves tandem mass spectrometry proteotyping.
| S-EPMC6742703 | biostudies-literature
Project description:BackgroundSample preparation is a critical process for proteomic studies. Many efficient and reproducible sample preparation methods have been developed for mass spectrometry-based proteomic analysis of human and animal tissues or cells, but no attempt has been made to evaluate these protocols for plants. We here present an LC-MS/MS-based proteomics study of barley leaf aimed at optimization of methods to achieve efficient and unbiased trypsin digestion of proteins prior to LC-MS/MS based sequencing and quantification of peptides. We evaluated two spin filter-aided sample preparation protocols using either sodium dodecyl-sulphate or sodium deoxycholate (SDC), and three in-solution digestion (ISD) protocols using SDC or trichloroacetic acid/acetone precipitation.ResultsThe proteomics workflow identified and quantified up to 1800 barley proteins based on sequencing of up to 6900 peptides per sample. The two spin filter-based protocols provided a 12-38% higher efficiency than the ISD protocols, including more proteins of low abundance. Among the ISD protocols, a simple one-step reduction and S-alkylation method (OP-ISD) was the most efficient for barley leaf sample preparation; it identified and quantified 1500 proteins and displayed higher peptide-to-protein inference ratio and higher average amino acid sequence coverage of proteins. The two spin filter-aided sample preparation protocols are compatible with TMT labelling for quantitative proteomics studies. They exhibited complementary performance as about 30% of the proteins were identified by either one or the other protocol, but also demonstrated a positive bias for membrane proteins when using SDC as detergent.ConclusionsWe provide detailed protocols for efficient plant protein sample preparation for LC-MS/MS-based proteomics studies. Spin filter-based protocols are the most efficient for the preparation of leaf samples for MS-based proteomics. However, a simple protocol provides comparable results although with different peptide digestion profile.
| S-EPMC6109330 | biostudies-literature
Project description:The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.
2019-06-13 | MTBLS623 | MetaboLights
Project description:We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540-660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390-540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5-25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.
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Project description:Recently, the increasing emergency of traffic accidents and the unsatisfactory outcome of surgical intervention are driving research to seek a novel technology to repair traumatic soft tissue injury. From this perspective, decellularized matrix grafts (ECM‑G) including natural ECM materials, and their prepared hydrogels and bioscaffolds, have emerged as possible alternatives for tissue engineering and regenerative medicine. Over the past decades, several physical and chemical decellularization methods have been used extensively to deal with different tissues/organs in an attempt to carefully remove cellular antigens while maintaining the non‑immunogenic ECM components. It is anticipated that when the decellularized biomaterials are seeded with cells in vitro or incorporated into irregularly shaped defects in vivo, they can provide the appropriate biomechanical and biochemical conditions for directing cell behavior and tissue remodeling. The aim of this review is to first summarize the characteristics of ECM‑G and describe their major decellularization methods from different sources, followed by analysis of how the bioactive factors and undesired residual cellular compositions influence the biologic function and host tissue response following implantation. Lastly, we also provide an overview of the in vivo application of ECM‑G in facilitating tissue repair and remodeling.
| S-EPMC7797433 | biostudies-literature
Project description:Identification and evaluation of proteins in the extracellular matrix (ECM) has proved challenging due to the insolubility of the bulk of ECM proteins in traditional proteomic extraction buffers. Multiple ECM-focused proteomic workflows have been developed over the past 10 years. These methods rely on decellularization followed by chaotrope extraction and ultimately enzymatic or chemical digestion. To date, there has not been a side-by-side comparison of all current methods on uniform, complex tissue samples. Herein, we present an evaluation of ECM-specific methods alongside several single-shot methods for tissue analysis. We provide recommendations for method selection based on ECM protein identification and sequence coverage as well as the ease and precision of the given methods.
2020-10-01 | MSV000086224 | MassIVE