Dataset for suppressors of amyloid-beta toxicity and their functions in recombinant protein production in yeast
Artikel i vetenskaplig tidskrift, 2022

The production of recombinant proteins at high levels often induces stress-related phenotypes by protein misfolding or aggregation. These are similar to those of the yeast Alzheimer's disease (AD) model in which amyloid-beta peptides (A beta 42) were accumulated [1,2] . We have previously identified suppressors of A beta 42 cytotoxicity via the genome-wide synthetic genetic array (SGA) [3] and here we use them as metabolic engineering targets to evaluate their potentiality on recombinant protein production in yeast Saccharomyces cerevisiae. In order to investigate the mechanisms linking the genetic modifications to the improved recombinant protein production, we perform systems biology approaches (transcriptomics and proteomics) on the resulting strain and intermediate strains. The RNAseq data are preprocessed by the nf-core/RNAseq pipeline and analyzed using the Platform for Integrative Analysis of Omics (PIANO) package [4] . The quantitative proteome is analyzed on an Orbitrap Fusion Lumos mass spectrometer interfaced with an Easy-nLC1200 liquid chromatography (LC) system. LC-MS data files are processed by Proteome Discoverer version 2.4 with Mascot 2.5.1 as a database search engine. The original data presented in this work can be found in the research paper titled "Suppressors of Amyloid-beta Toxicity Improve Recombinant Protein Produc-tion in yeast by Reducing Oxidative Stress and Tuning Cellu-lar Metabolism", by Chen et al. [5] .

Gene engineering

Proteome

Amyloid-beta

Transcriptome

Yeast Saccharomyces cerevisiae

Författare

Xin Chen

Chalmers, Biologi och bioteknik, Systembiologi

Xiaowei Li

Chalmers, Biologi och bioteknik, Systembiologi

Boyang Ji

Chalmers, Biologi och bioteknik, Systembiologi

Yanyan Wang

Chalmers, Biologi och bioteknik, Systembiologi

Olena Ishchuk

Chalmers, Biologi och bioteknik, Systembiologi

Egor Vorontsov

Göteborgs universitet

Dina Petranovic Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

Verena Siewers

Chalmers, Biologi och bioteknik, Systembiologi

Martin Engqvist

Chalmers, Biologi och bioteknik, Systembiologi

Data in Brief

23523409 (eISSN)

Vol. 42 108322

Ämneskategorier

Biokemi och molekylärbiologi

Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)

Bioinformatik och systembiologi

DOI

10.1016/j.dib.2022.108322

PubMed

35677454

Mer information

Senast uppdaterat

2022-06-28