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Supplemental Material for Juurakko et al., 2021

dataset
posted on 2021-06-08, 15:40 authored by Collin L. Juurakko, Melissa Bredow, Takato Nakayama, Hiroyuki Imai, Yukio Kawamura, George C. diCenzo, Matsuo Uemura, Virginia K. Walker

File S1 contains all scripts and code used for the analysis of the Brachypodium cold-acclimated PM proteome. File S2 contains the stress response network meta-analysis for the CA2 dataset of the Brachypodium PM proteome. File S3 contains the total raw Brachypodium PM proteome dataset. File S4 contains the significantly increased Brachypodium PM protein dataset. File S5 contains the significantly decreased Brachypodium PM protein dataset. File S6 contains the CA2 decreased annotated Brachypodium PM protein dataset. File S7 contains the CA6 decreased annotated Brachypodium PM protein dataset. File S8 contains the CA2 increased annotated Brachypodium PM protein dataset. File S9 contains the CA6 increased annotated Brachypodium PM protein dataset. File S10 contains the interactive network for the stress response meta-analysis of Brachypodium CA2 proteins. File S11 contains the interactive network for the CA2 predicted protein-protein interactions. File S12 contains the interactive network for the CA6 predicted protein-protein interactions. File S13 contains the CA2 preliminary Brachypodium PM dataset.


Protein descriptions were manually predicted using UniProt (UniProt Consortium), RIKEN Brachypodium FLcDNA database (Mochida et al. 2013), BLAST, and through literature searches. PM localizations were predicted using UniProt, TMHMM Server (version 2.0) for transmembrane helices (Krogh et al. 2001), GPS-lipid for N-myristoylation/-palmitylation sites, DeepLoc-1.0 (http://www.cbs.dtu.dk/services/DeepLoc-1.0/) (Almagro Armenteros et al. 2019), BUSCA (http://busca.biocomp.unibo.it/) (Savojardo et al. 2018), WolF PSORT (https://wolfpsort.hgc.jp/) (Horton et al. 2007), and known localization of orthologous plant proteins. Localization to other compartments was predicted using Uniprot (UniProt Consortium) and SignalP 5.0 (http://www.cbs.dtu.dk/services/SignalP/) (Almagro Armenteros et al. 2019) for localization to the extracellular space, mitochondria, and chloroplasts. Proteins were classified based on the functional categories as described by Bevan et al. (1998) and Miki et al. (2019).

A list of protein accession identifications for all significantly increased and decreased proteins obtained by MS were assembled and used as inputs for STRING (version 11.0) to predict protein-protein interactions (Franceschini et al. 2016; Szklarczyk et al. 2019) for CA2 and CA6 timepoints. A predicted network was prepared and exported to Cytoscape (version 3.8.1) for further modification. Additional protein metadata was input into Cytoscape including corresponding log2 fold-change values which were assigned to node fill mapping.

To construct a stress response meta-analysis network, individual protein accession identifications were subjected to literature searches (performed to 1/1/2021) and annotated according to their protein descriptions and involvement in stress response pathways (File S2). Proteins with no reported involvement in stress responses were omitted. The dataset was then input into Cytoscape with and log2 fold-changes were again selected as node fill mapping as described previously. All networks were centred in the plot area and exported as Scalable Vector Graphics (SVG) files where further modification was performed and legends added in Inkscape (version 0.92.2). Interactive versions of each network were additionally exported as full webpages for viewing in any modern web browser as HTML files with all metadata.

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Article title

The Brachypodium distachyon cold-acclimated plasma membrane proteome is primed for stress resistance