Evidence map›Paper›PMID 29915279›Full record

ArticleScientific reports2018

MS analysis of a dilution series of bacteria:phytoplankton to improve detection of low abundance bacterial peptides.

Emma Timmins-Schiffman, Molly P Mikan, Ying Sonia Ting, H Rodger Harvey, Brook L Nunn

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Emma Timmins-SchiffmanUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.ORCID 0000-0002-2478-6541
Molly P MikanOld Dominion University, Department of Ocean, Earth, and Atmospheric Sciences, Norfolk, VA, 23529, USA.
Ying Sonia TingUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.ORCID 0000-0003-2492-3718
H Rodger HarveyOld Dominion University, Department of Ocean, Earth, and Atmospheric Sciences, Norfolk, VA, 23529, USA.
Brook L NunnUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA. brookh@uw.edu.

Funding

INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
NHGRI NIH HHS T32 HG000035
6 · The paper itself

Abstract

Assigning links between microbial activity and biogeochemical cycles in the ocean is a primary objective for ecologists and oceanographers. Bacteria represent a small ecosystem component by mass, but act as the nexus for both nutrient transformation and organic matter recycling. There are limited methods to explore the full suite of active bacterial proteins largely responsible for degradation. Mass spectrometry (MS)-based proteomics now has the potential to document bacterial physiology within these complex systems. Global proteome profiling using MS, known as data dependent acquisition (DDA), is limited by the stochastic nature of ion selection, decreasing the detection of low abundance peptides. The suitability of MS-based proteomics methods in revealing bacterial signatures outnumbered by phytoplankton proteins was explored using a dilution series of pure bacteria (Ruegeria pomeroyi) and diatoms (Thalassiosira pseudonana). Two common acquisition strategies were utilized: DDA and selected reaction monitoring (SRM). SRM improved detection of bacterial peptides at low bacterial cellular abundance that were undetectable with DDA from a wide range of physiological processes (e.g. amino acid synthesis, lipid metabolism, and transport). We demonstrate the benefits and drawbacks of two different proteomic approaches for investigating species-specific physiological processes across relative abundances of bacteria that vary by orders of magnitude.

Indexed as

BacteriaBiomarkersDiatomsMass SpectrometryPeptidesPhytoplanktonProteomicsBiomarkersPeptides

Identifiers

PMID29915279
PMCPMC6006377

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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.