Evidence map›Paper›PMID 25883932›Full record

ArticleFrontiers in bioengineering and biotechnology2015

Standard flow liquid chromatography for shotgun proteomics in bioenergy research.

Susana M González Fernández-Niño, A Michelle Smith-Moritz, Leanne Jade G Chan, Paul D Adams, Joshua L Heazlewood, Christopher J Petzold

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

26 citing papers in PubMed, 53 citations in OpenAlex.

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  9. Production of tetra-methylpyrazine using engineeredMetabolic engineering communications · 2020
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  16. Biosynthesis and secretion of the microbial sulfated peptide RaxX and binding to the rice XA21 immune receptor.Proceedings of the National Academy of Sciences of the United States of America · 2019
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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

6 authors at 2 institutions in 2 countries.

Susana M González Fernández-NiñoJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA.
A Michelle Smith-MoritzJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA.
Leanne Jade G ChanJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA.
Paul D AdamsJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA ; Department of Bioengineering, University of California Berkeley , Berkeley, CA , USA.
Joshua L HeazlewoodJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA ; Australian Research Council Centre of Excellence in Plant Cell Walls, School of Botany, The University of Melbourne , Melbourne, VIC , Australia.
Christopher J PetzoldJoint BioEnergy Institute and Physical Biosciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA , USA.
Lawrence Berkeley National Laboratory · USUniversity of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past 10 years, the bioenergy field has realized significant achievements that have encouraged many follow on efforts centered on biosynthetic production of fuel-like compounds. Key to the success of these efforts has been transformational developments in feedstock characterization and metabolic engineering of biofuel-producing microbes. Lagging far behind these advancements are analytical methods to characterize and quantify systems of interest to the bioenergy field. In particular, the utilization of proteomics, while valuable for identifying novel enzymes and diagnosing problems associated with biofuel-producing microbes, is limited by a lack of robustness and limited throughput. Nano-flow liquid chromatography coupled to high-mass accuracy, high-resolution mass spectrometers has become the dominant approach for the analysis of complex proteomic samples, yet such assays still require dedicated experts for data acquisition, analysis, and instrument upkeep. The recent adoption of standard flow chromatography (ca. 0.5 mL/min) for targeted proteomics has highlighted the robust nature and increased throughput of this approach for sample analysis. Consequently, we assessed the applicability of standard flow liquid chromatography for shotgun proteomics using samples from Escherichia coli and Arabidopsis thaliana, organisms commonly used as model systems for lignocellulosic biofuels research. Employing 120 min gradients with standard flow chromatography, we were able to routinely identify nearly 800 proteins from E. coli samples; while for samples from Arabidopsis, over 1,000 proteins could be reliably identified. An examination of identified peptides indicated that the method was suitable for reproducible applications in shotgun proteomics. Standard flow liquid chromatography for shotgun proteomics provides a robust approach for the analysis of complex samples. To the best of our knowledge, this study represents the first attempt to validate the standard flow approach for shotgun proteomics.

Indexed as

biofuelsmass spectrometryproteomicsstandard flow chromatography

Identifiers

PMID25883932
PMCPMC4381839
OpenAlexW2052429732

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.