Evidence map›Paper›PMID 23028060›Full record

ArticleMolecular & cellular proteomics : MCP2012

High-definition de novo sequencing of crustacean hyperglycemic hormone (CHH)-family neuropeptides.

Chenxi Jia, Limei Hui, Weifeng Cao, Christopher B Lietz, Xiaoyue Jiang, Ruibing Chen, Adam D Catherman, Paul M Thomas, Ying Ge, Neil L Kelleher and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.0field-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

17 citing papers in PubMed, 36 citations in OpenAlex.

  1. Review
  2. Neuropeptidomics of the American LobsterJournal of proteome research · 2024
    Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Identification, Quantitation, and Imaging of the Crustacean Peptidome.Methods in molecular biology (Clifton, N.J.) · 2018
    Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Small-volume analysis of cell-cell signaling molecules in the brain.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2014
    Review
  15. Article
  16. Article
  17. Review
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

11 authors at 2 institutions in 1 country.

Chenxi JiaSchool of Pharmacy and Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA.
Limei Hui
Weifeng Cao
Christopher B Lietz
Xiaoyue Jiang
Ruibing Chen
Adam D Catherman
Paul M Thomas
Ying Ge
Neil L Kelleher
Lingjun Li
University of Wisconsin–Madison · USNorthwestern University · US

Funding

The UIUC Neuroproteomics Center on Cell-Cell SignalingP30DA018310 · NIDA · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Elena V Romanova · 2004 to 2026
$24.9M
Mass Spectrometric Studies of Neuropeptides in FeedingR01DK071801 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2006 to 2026
$6.7M
Eukaryotic Post-Translational ModificationsR01GM067193 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI KELLEHER, NEIL L · 2003 to 2015
$4.0M
Top Down Proteomics Of Myofilaments In Heart FailureR01HL096971 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2011 to 2021
$3.3M
NHLBI NIH HHS R01 HL096971NHLBI NIH HHS R01HL096971NIDA NIH HHS P30 DA018310NIDDK NIH HHS R01 DK071801NIDDK NIH HHS R01DK071801NIGMS NIH HHS R01 GM067193
6 · The paper itself

Abstract

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8-9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.

Indexed as

BrachyuraAmino Acid SequenceAnimalsArthropod ProteinsInvertebrate HormonesMass SpectrometryMolecular Sequence DataNerve Tissue ProteinsProtein ConformationProtein Processing, Post-TranslationalSequence AlignmentSequence Analysis, ProteinSignal TransductionSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationArthropod Proteinshyperglycemic hormone, crustaceanInvertebrate HormonesNerve Tissue Proteins

Identifiers

PMID23028060
PMCPMC3518134
OpenAlexW1989457128

What OpenQuestion holds

Textmetadata
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.