Evidence map›Paper›PMID 28605387›Full record

ArticleJournal of visualized experiments : JoVE2017

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample.

Mohamed Salem, Michal Bernach, Krzysztof Bajdzienko, Patrick Giavalisco

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 66 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 2 countries.

Mohamed SalemMax Planck Institute of Molecular Plant Physiology, Golm, Germany; Department of Pharmacognosy, Faculty of Pharmacy, Cairo University.
Michal BernachMax Planck Institute of Molecular Plant Physiology, Golm, Germany.
Krzysztof BajdzienkoMax Planck Institute of Molecular Plant Physiology, Golm, Germany.
Patrick GiavaliscoMax Planck Institute of Molecular Plant Physiology, Golm, Germany; giavalisco@mpimp-golm.mpg.de.
Max Planck Institute of Molecular Plant Physiology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

Indexed as

ArabidopsisChromatography, GasChromatography, LiquidLipidsMass SpectrometryMetabolomicsProteinsProteomicsLipidsProteins

Identifiers

PMID28605387
PMCPMC5608179
OpenAlexW2620635959

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.