Scope

Plant Proteomics and Protein Structural Biology section publishes significant findings and major advances in the field of protein-based regulation of biological processes, specifically focusing on proteome-wide and structural biology studies that examine the dynamics, functions, and interactions of proteins from plant systems.

Topics covered by this section include, but are not limited to:

• · Comparative proteomic studies employing 2-DE, labeling, or unlabeled strategies
• · Characterization of subcellular, cellular, or plant organ proteomes
• · Characterization of protein modifications by mass spectrometry
• · Protein-protein interactions and protein networks
• · Protein cross-linking studies using mass spectrometry
• · Bioinformatic analysis of proteomic data, including new online resources and tools
• · Novel or improved methods involving mass spectrometry
• · Structural characterization and analysis of proteins, using secondary structure determination techniques, small-angle scattering techniques, X-ray crystallography, NMR spectroscopy, and electron microscopy to explore molecular structure and dynamics of proteins and how alterations in their structure affect their function
• · Protein modeling if validated by experimental data
• · In-depth phylogenetic studies, i.e. studying the evolutionary relationships between species, that focus on protein classes related to signal transduction, such as those regulating phosphorylation, ubiquitination, sumoylation, etc.
• · Large-scale bio-informatic surveys comparing (evolutionarily conserved) sites for regulatory PTMs across species

Descriptive studies that present a list of differentially abundant proteins (DAPs), so merely cataloging, in response to different conditions or treatments or as comparison of different species do not fall under the scope of the section unless they are extended to elaborate on a new pathway or biological process related to the treatment or to the species presented. Submissions to the section are expected to comply with the technical requirements for proteomics studies as indicated in the author guidelines (here). Proteomic surveys should be of sufficient depth to address the process being examined and validation of key DAPs should be presented. Phylogenetic studies or large-scale bio-informatic surveys should not merely simply catalog a protein family in a few (exotic) species but should provide a thorough analysis within (at least) the Viridiplantae.

Please consider the content and quality requirements for experimental studies as listed below:

Quantitative analysis needs to be performed on a minimum number of 3 biological replicates in order to enable an assessment of significance. This includes quantitative omics studies (transcriptomics, proteomics, metabolomics) as well as phenotypic measurements, quantitative assays, and qPCR expression analysis. Studies that do not comply with these replication requirements will not be considered for review.

Studies falling into the categories below will not be considered for review unless they are expanded and provide insight into the biological system or process being studied:

i) Descriptive collection of transcripts, proteins or metabolites, including comparative sets as a result of different conditions or treatments;

ii) Descriptive studies that define gene families using basic phylogenetics and the assignment of cursory functional attributions (e.g. expression profiles, hormoner />or metabolites levels, promoter analysis, informatic parameters).

Studies using transgenic or mutant plants should be based on data from multiple independent alleles (at least 2) displaying a common and stable phenotype. Examples include T-DNA, transposon, RNAi, CRISPR/Cas9, chemically induced, overexpressors, reporter fusions (GUS, FPs, LUC) etc. Qualitative data can be presented from a single allele but should be indicative of observations from multiple alleles which should be explicitly stated in the text. Quantitative data should be derived from multiple alleles (at least 2) and should be displayed separately for each allele (with at least 3 independent replications for each allele). Studies reporting single alleles may be considered acceptable when:

i) Complementation via transformation is used for confirmation;
ii) The allele has been previously characterized and published and is representative of multiple independent lines;
iii) Systems where genetic transformation is difficult or not yet possible, alternative evidence should be presented supporting the reported allele.

Submission

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