Evidence map›Paper›PMID 25617659›Full record

ReviewBiochimica et biophysica acta2015

Mass spectrometry-based characterization of endogenous peptides and metabolites in small volume samples.

Ta-Hsuan Ong, Emily G Tillmaand, Monika Makurath, Stanislav S Rubakhin, Jonathan V Sweedler

Abstract readReview
In one paragraph

Review in Biochimica et biophysica acta, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Peptidomics.Nature reviews. Methods primers · 2023
    Article
  2. Article
  3. Article
  4. Article
  5. Neuropeptidomics of the Rat Habenular Nuclei.Journal of proteome research · 2018
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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.

Ta-Hsuan OngDepartment of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Emily G TillmaandDepartment of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Monika MakurathDepartment of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Stanislav S RubakhinDepartment of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Jonathan V SweedlerDepartment of Chemistry and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States. Electronic address: jsweedle@illinois.edu.

Funding

The UIUC Neuroproteomics Center on Cell-Cell SignalingP30DA018310 · NIDA · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Elena V Romanova · 2004 to 2026
$24.9M
SUBCELLULAR CHARACTERIZATION OF NEUROTRANSMITTERSR01NS031609 · NINDS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI SWEEDLER, JONATHAN V. · 1998 to 2022
$6.2M
NEUROTRANSMITTER RELEASER29NS031609 · NINDS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI SWEEDLER, JONATHAN V. · 1993 to 1997
–
NIDA NIH HHS P30 DA018310NIDA NIH HHS P30 DA18310NINDS NIH HHS NS031609NINDS NIH HHS R01 NS031609
6 · The paper itself

Abstract

Technologies to assay single cells and their extracellular microenvironments are valuable in elucidating biological function, but there are challenges. Sample volumes are low, the physicochemical parameters of the analytes vary widely, and the cellular environment is chemically complex. In addition, the inherent difficulty of isolating individual cells and handling small volume samples complicates many experimental protocols. Here we highlight a number of mass spectrometry (MS)-based measurement approaches for characterizing the chemical content of small volume analytes, with a focus on methods used to detect intracellular and extracellular metabolites and peptides from samples as small as individual cells. MS has become one of the most effective means for analyzing small biological samples due to its high sensitivity, low analyte consumption, compatibility with a wide array of sampling approaches, and ability to detect a large number of analytes with different properties without preselection. Having access to a flexible portfolio of MS-based methods allows quantitative, qualitative, untargeted, targeted, multiplexed, and spatially resolved investigations of single cells and their similarly scaled extracellular environments. Combining MS with on-line and off-line sample conditioning tools, such as microfluidic and capillary electrophoresis systems, significantly increases the analytical coverage of the sample's metabolome and peptidome, and improves individual analyte characterization/identification. Small volume assays help to reveal the causes and manifestations of biological and pathological variability, as well as the functional heterogeneity of individual cells within their microenvironments and within cellular populations. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Indexed as

AnimalsHumansMass SpectrometryPeptidesPeptidesBioanalytical microanalysisMass spectrometryMicroenvironmentsSingle cell

Identifiers

PMID25617659
PMCPMC4426231

What OpenQuestion holds

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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.