Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

Anne Mathilde Lund; Christian Schrøder Kaas; Julian Brandl; Lasse Ebdrup Pedersen; Helene Faustrup Kildegaard; Claus Kristensen; Mikael Rørdam Andersen

doi:10.1186/s12918-017-0414-4

Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

Anne Mathilde Lund, Christian Schrøder Kaas, Julian Brandl, Lasse Ebdrup Pedersen, Helene Faustrup Kildegaard, Claus Kristensen, Mikael Rørdam Andersen^*

^*Corresponding author for this work

Glycomics Program

7 Citations (Scopus)

56 Downloads (Pure)

Abstract

Background: Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology. Results: On the basis of manual curation of the literature on the yeast, human, and mouse secretory pathway, we have compiled a comprehensive catalogue of characterized proteins with functional annotation and their interconnectivity. Thus we have established the most elaborate reconstruction (RECON) of the functional secretion pathway network to date, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional regulation of protein secretion than healthy mouse cells. Conclusions: The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein production.

Original language	English
Article number	37
Journal	BMC Systems Biology
Volume	11
Issue number	1
Number of pages	17
ISSN	1752-0509
DOIs	https://doi.org/10.1186/s12918-017-0414-4
Publication status	Published - 15 Mar 2017

Keywords

Chinese hamster ovary cells
Pathway reconstruction
Protein secretion
RNA-Seq
Secretion pathway

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1186/s12918-017-0414-4Licence: CC BY

Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome dataFinal published version, 3.75 MBLicence: CC BY

Cite this

@article{7a48f042480d4c8da3eac66a9d53ba97,

title = "Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data",

abstract = "Background: Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology. Results: On the basis of manual curation of the literature on the yeast, human, and mouse secretory pathway, we have compiled a comprehensive catalogue of characterized proteins with functional annotation and their interconnectivity. Thus we have established the most elaborate reconstruction (RECON) of the functional secretion pathway network to date, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional regulation of protein secretion than healthy mouse cells. Conclusions: The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein production.",

keywords = "Chinese hamster ovary cells, Pathway reconstruction, Protein secretion, RNA-Seq, Secretion pathway",

author = "Lund, {Anne Mathilde} and Kaas, {Christian Schr{\o}der} and Julian Brandl and Pedersen, {Lasse Ebdrup} and Kildegaard, {Helene Faustrup} and Claus Kristensen and Andersen, {Mikael R{\o}rdam}",

year = "2017",

month = mar,

day = "15",

doi = "10.1186/s12918-017-0414-4",

language = "English",

volume = "11",

journal = "B M C Systems Biology",

issn = "1752-0509",

publisher = "BioMed Central Ltd.",

number = "1",

}

TY - JOUR

T1 - Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

AU - Lund, Anne Mathilde

AU - Kaas, Christian Schrøder

AU - Brandl, Julian

AU - Pedersen, Lasse Ebdrup

AU - Kildegaard, Helene Faustrup

AU - Kristensen, Claus

AU - Andersen, Mikael Rørdam

PY - 2017/3/15

Y1 - 2017/3/15

N2 - Background: Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology. Results: On the basis of manual curation of the literature on the yeast, human, and mouse secretory pathway, we have compiled a comprehensive catalogue of characterized proteins with functional annotation and their interconnectivity. Thus we have established the most elaborate reconstruction (RECON) of the functional secretion pathway network to date, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional regulation of protein secretion than healthy mouse cells. Conclusions: The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein production.

AB - Background: Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology. Results: On the basis of manual curation of the literature on the yeast, human, and mouse secretory pathway, we have compiled a comprehensive catalogue of characterized proteins with functional annotation and their interconnectivity. Thus we have established the most elaborate reconstruction (RECON) of the functional secretion pathway network to date, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional regulation of protein secretion than healthy mouse cells. Conclusions: The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein production.

KW - Chinese hamster ovary cells

KW - Pathway reconstruction

KW - Protein secretion

KW - RNA-Seq

KW - Secretion pathway

UR - http://www.scopus.com/inward/record.url?scp=85015185353&partnerID=8YFLogxK

U2 - 10.1186/s12918-017-0414-4

DO - 10.1186/s12918-017-0414-4

M3 - Journal article

C2 - 28298216

AN - SCOPUS:85015185353

SN - 1752-0509

VL - 11

JO - B M C Systems Biology

JF - B M C Systems Biology

IS - 1

M1 - 37

ER -

Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this