Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Leaf protein extraction method

ABSTRACT: We evaluated several approaches for sample processing that are based on popular urea extraction, methanol/chloroform, and phenol methods. Additionally, we examined whether these methods were improved using FASP-based on filter digestion. We found that phenol-FASP and UA-FASP methods enabled the best coverage of protein, peptides, and MS/MS

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Arabidopsis Thaliana (ncbitaxon:3702)

SUBMITTER: Justin Walley

PROVIDER: MSV000082080 | MassIVE | Tue Feb 20 13:39:00 GMT 2018

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Assessment and Refinement of Sample Preparation Methods for Deep and Quantitative Plant Proteome Profiling.

Song Gaoyuan G Hsu Polly Yingshan PY Walley Justin W JW

Proteomics 20180827 17

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 quantificat ...[more]

PMID: 30035338

Similar Datasets

Arabidopsis Root Protein Extraction Evaluation

Project description:We evaluated several approaches for sample processing that are based on popular urea extraction, methanol/chloroform, and phenol methods. Additionally, we examined whether these methods were improved using FASP-based on filter digestion. We found that phenol-FASP and UA-FASP methods enabled the best coverage of protein, peptides, and MS/MS.

2018-05-15 | MSV000082362 | MassIVE

Parallel protein extraction methods increase the diversity of protein identification in Park Grass Experiment soil

Project description:We have combined a modified protein extraction method, heat/thaw/phenol/chloroform (HTPC), with the established Surfactant extraction method to identify proteins from Park Grass Experiment (PGE) soil, which has an extensively sequenced microbial database.

2022-09-20 | PXD017392 | Pride

Optimization of Protein Isolation and Label–free Quantitative Proteomic Analysis in Four Different Tissues of Korean Ginseng

Project description:Korean ginseng is one of the most valuable medicinal plants worldwide. Yet, our understanding of ginseng proteomics is largely limited due to difficulties in extraction and resolution of ginseng proteins because of the presence of natural contaminants such as polysaccharides, phenols, and glycosides. Here, we compared four different protein extraction methods, namely, TCA/acetone, TCA/acetone–MeOH/chloroform, Phenol–TCA/acetone, and Phenol–MeOH/chloroform methods. Consequently, the TCA/acetone–MeOH/chloroform method displayed the highest extraction efficiency, thus it was used for the comparative proteome profiling of leaf, root, shoot, and fruit by a label–free quantitative proteomics approach. This approach led to the identification of 2,604 significantly modulated proteins among four tissues. We could pinpoint differential pathways and proteins associated with ginsenoside biosynthesis including the methylerythritol 4–phosphate (MEP) pathway, the mevalonate (MVA) pathway, UDP–glycosyltransferases (UGTs), and oxidoreductases (CYP450s). The current study reports an efficient and reproducible method for the isolation of proteins from a wide range of ginseng tissues and provides a detailed organ–based proteome map and a more comprehensive view of enzymatic alterations in ginsenoside biosynthesis.

2021-09-07 | PXD022914 | Pride

Project description:Bacterial diveristy of Sardinella gut microbiome: Phenol:chloroform method

| PRJNA428792 | ENA

Three protein extraction methods for mass spectrometry proteomics of fresh frozen mouse tissue

Project description:We present three different methods for protein extraction from fresh frozen mouse heart tissue: 1) extraction using SDS buffer followed by FASP purification, 2) extraction using SDS buffer followed by S-Trap purification, and 3) extraction using a guanidine hydrochloride buffer followed by in-solution digestion. Based on bicinchoninic acid assay, all three methods display similar recovery of total protein content. However, proteomics-based analysis identified far fewer proteins from the extraction guanidine hydrochloride. SDS-FASP identifies as many proteins as the SDS-STrap method with good coverage of proteins from different cellular compartments.

2020-07-30 | PXD020256 | Pride

UPA-Seq: Prediction of functional lncRNAs using the sensitivities to UV-crosslinking

Project description:Assuming that functional lncRNAs form larger ribonucleoprotein complex and thus are easily crosslinked to proteins upon UV-irradiation, we performed RNA-Seq analyses of RNAs recovered from the aqueous phase after the UV-irradiation and phenol chloroform extraction (UPA-Seq)

2018-09-21 | GSE114789 | GEO

Surfactant and chaotropic agent assisted sequential extraction/on pellet digestion (SCAD) for enhanced proteomics

Project description:As a popular sample preparation approach, Filter-aided sample preparation (FASP) has been widely used in proteomic analysis. However, several limitations have been noted, including sample loss during filtration, repetitive centrifugation steps, and the possibility of breakage of filtration membrane. Extraction bias among different sample preparation strategies is another challenging question. To overcome these limitations and address remaining challenges, we developed a novel surfactant and chaotropic agent assisted sequential extraction/on pellet digestion (SCAD) protocol. The new strategy resulted in higher protein yield, improved peptide recovery and protein coverage compared to two conventional sample preparation methods (FASP and urea). In combination of three strategies, more than 10,000 distinct protein groups were identified with 1% FDR from MDA-MB-231 cells without any pre-fractionation. This in-depth proteome analysis was accomplished by optimization of protein extraction, enzymatic digestion, LC gradient and peptide sequencing method. IPA analysis of protein exclusively identified in SCAD revealed several crucial signaling pathways which regulate breast cancer progression. An unbiased extraction of different categories of proteins associated with tumorigenesis was also demonstrated. This novel strategy not only expedites comprehensive protein identification but also post-translational modifications (PTMs) of proteins (e.g., glycosylation), thus is applicable for biomarker discovery in various types of cancers.

2018-10-19 | PXD008967 | Pride

Milk bottom-up proteomics: method optimisation.

Project description:Milk is a complex fluid whose proteome displays a diverse set of proteins of high abundance such as caseins and medium to low abundance whey proteins such as ß-lactoglobulin, lactoferrin, immunoglobulins, glycoproteins, peptide hormones and enzymes. A sample preparation method that enables high reproducibility and throughput is key in reliably identifying proteins present or proteins responding to conditions such as a diet, health or genetics. Using skim milk samples from Jersey and Holstein cows, we compared three extraction procedures which have not previously been applied to samples of cows’ milk. Method A (urea) involved a simple dilution of the milk in a urea-based buffer, method B (TCA/acetone) involved a TCA/acetone precipitation and method C (methanol/chloroform) involved a tri-phasic partition method in chloroform/methanol solution. Protein assays, SDS-PAGE profiling, and trypsin digestion followed by nanoHPLC-electrospray ionisation-tandem mass spectrometry (nLC-ESI-MS/MS) analyses were performed to assess their efficiency. Replicates were used at each analytical step (extraction, digestion, injection) to assess reproducibility. Overall 186 unique accessions, major and minor proteins, were identified with a combination of methods. Method C (methanol/chloroform) yielded the best resolved SDS-patterns and highest protein recovery rates, method A (urea) yielded the greatest number of accessions, and, of the three procedures, method B (TCA/acetone) was the least compatible of all with a wide range of downstream analytical procedures. Our results also highlighted breed differences between the proteins in milk of Jersey and Holstein cows.

2016-01-26 | PXD002529 | Pride

Genomewide demarcation of RNA PolII transcription units by physical fractionation of chromatin- Neutral enrichment

Project description:Epigenetic modifications of chromatin serve an important role in regulating the expression and accessibility of genomic DNA. We report here a genomewide approach for fractionating yeast chromatin into two functionally distinct parts, one containing RNA polymerase II transcribed sequences, and the other comprising noncoding sequences and genes transcribed by RNA polymerases I and III. Noncoding regions could be further fractionated into promoters and segments lacking promoters. The observed separations were apparently based on differential crosslinking efficiency of chromatin in different genomic regions. The results reveal a genomewide molecular mechanism for marking promoters and genomic regions that have a license to be transcribed by RNA polymerase II, a previously unrecognized level of genomic complexity that may exist in all eukaryotes. Our approach has broad potential use as a tool for genome annotation and for the characterization of global changes in chromatin structure that accompany different genetic, environmental, and disease states. Keywords: Genomewide mapping of regulatory elements through differential fractionation of crosslinked chromatin based on nucleosome occupancy. Neutral enrichment- All DNA was prepared by glass-bead disruption and standard phenol-chloroform extraction with the modification that the cells were first broken in the absence of phenol-chloroform. The extract was centrifuged for 5 s at 14,000Xg, and the supernatant was sonicated and subsequently phenol-chloroform extracted.

2010-07-01 | E-GEOD-5651 | biostudies-arrayexpress

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liq-uid Chromatography Tandem Mass Spectrometry

Project description:Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis and for a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and pro-teomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently used solvent systems: chloro-form/methanol and methanol-only. Whole blood samples were collected from participants (n=6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods i. methanol precipitation and, ii. 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

2023-01-17 | PXD038750 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data