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Peptide Identification Using Tandem Mass Spectrometry

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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MtSSPdb: The Medicago truncatula Small Secreted Peptide Database.

Clarissa Boschiero¹, Xinbin Dai¹, Peter Knut Lundquist^1,2

¹Noble Research Institute, Ardmore, Oklahoma 73401.

Plant Physiology

|February 22, 2020

Summary

Plant small secreted peptides (SSPs) regulate crucial processes. We developed the Medicago truncatula Small Secreted Peptide Database (MtSSPdb) to aid research on these vital plant regulatory molecules.

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Peptide-based Identification of Functional Motifs and their Binding Partners

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Area of Science:

Plant molecular biology
Genomics
Bioinformatics

Background:

Small secreted peptides (SSPs) are key regulators in plant growth, development, reproduction, stress, and defense.
SSPs are crucial for legume root nodule development.
SSP-encoding genes are often missed by standard genome annotation due to small open reading frames and low/specific expression.

Purpose of the Study:

To support the systematic characterization and annotation of small secreted peptide (SSP)-encoding genes in Medicago truncatula.
To provide a comprehensive resource for plant SSP research.

Main Methods:

Identification of 4,439 SSP-encoding genes in Medicago truncatula.
Development of the Medicago truncatula Small Secreted Peptide Database (MtSSPdb).
Integration of an RNA-sequencing-based gene expression atlas with analytical tools (differential expression, coexpression, pathway enrichment).
Inclusion of an online SSP prediction tool and data from synthetic peptide screens.

Main Results:

MtSSPdb hosts a compendium of Medicago truncatula SSP candidates with functional and family annotations.
The database includes a large-scale gene expression atlas with advanced analytical capabilities.
An online tool for genome-scale SSP prediction is available.
Data from synthetic peptide screens, including root and nodule phenotyping, are integrated.

Conclusions:

MtSSPdb is a unique and valuable resource for the plant research community.
The database facilitates systematic characterization and annotation of plant SSPs.
MtSSPdb has the potential to become the most complete database for plant SSPs globally.