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. 2017 Jun;101(12):5045-5058.
doi: 10.1007/s00253-017-8317-2. Epub 2017 May 22.

Insights into the prevalence and underlying causes of clonal variation through transcriptomic analysis in Pichia pastoris

Affiliations

Insights into the prevalence and underlying causes of clonal variation through transcriptomic analysis in Pichia pastoris

Rochelle Aw et al. Appl Microbiol Biotechnol. 2017 Jun.

Abstract

Clonal variation, wherein a range of specific productivities of secreted proteins are observed from supposedly identical transformants, is an accepted aspect of working with Pichia pastoris. It means that a significant number of transformants need to be tested to obtain a representative sample, and in commercial protein production, companies regularly screen thousands of transformants to select for the highest secretor. Here, we have undertaken a detailed investigation of this phenomenon by characterising clones transformed with the human serum albumin gene. The titers of nine clones, each containing a single copy of the human serum albumin gene (identified by qPCR), were measured and the clones grouped into three categories, namely, high-, mid- and low-level secretors. Transcriptomic analysis, using microarrays, showed that no regulatory patterns consistently correlated with titer, suggesting that the causes of clonal variation are varied. However, a number of physiological changes appeared to underlie the differences in titer, suggesting there is more than one biochemical signature for a high-secreting strain. An anomalous low-secreting strain displaying high transcript levels that appeared to be nutritionally starved further emphasises the complicated nature of clonal variation.

Keywords: Clonal variation; ER-associated degradation; Pichia pastoris/Komagataella phaffii; Protein expression; Transcriptomic analysis/microarray; Unfolded protein response.

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Conflict of interest statement

Competing interests

The authors declare that they have no competing interests.

Funding

Funding was provided to RA by Biotechnology and Biological Sciences Research Council (BBSRC) as a CASE studentship with Avecia Biologics Ltd. (now Fujifilm Diosynth Biotechnologies). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Figures

Fig. 1
Fig. 1
Correlation of secreted HSA titer with HSA and UPR-related transcript levels. Clones were expressed in triplicate for 24 h in methanol-containing medium in 250-mL baffled flasks. Green—high secretors, yellow—mid secretors and red—low secretors. a Secreted HSA titer levels of single copy HSA clones; error bars displayed indicate 95% confidence interval. b HSA transcript levels of single-copy HSA clones calculated by the ΔΔCt method in comparison to ACT1 as the housekeeping gene. c Correlation of HSA transcript level (fold change) with HSA titer (mg L−1). d Transcript levels of HAC1, KAR2 and PDI for each of the single-copy HSA clones calculated from transcriptomic analysis
Fig. 2
Fig. 2
FACS analysis of clonal variants grown for 24 h in methanol-containing medium. FL1-H: SYTO9® a green fluorescent nucleic acid stain indicating live cells, FL2-A: propidium iodide a red fluorescent stain indicating dead cells with a damaged membrane. BG background noise. Quadrant displays proportion of live/dead cells and background noise
Fig. 3
Fig. 3
Venn diagrams of upregulated or downregulated pathways in the H, M and L clones. The Venn diagrams indicate the number of KEGG-classified pathways that were significantly upregulated or downregulated in the H, M and L clones, determined by KOBAS pathway analysis. a Upregulated in high secretors. b Upregulated in mid secretors. c Upregulated in low secretors. d Downregulated in high secretors. e Downregulated in mid secretors. f Downregulated in low secretors
Fig. 4
Fig. 4
Expression levels of genes-encoding proteins involved in ribosomal proteins. Heat maps of log 2 normalised expression levels of genes-encoding ribosomal proteins, as defined by KEGG families, compared to those of wild-type after 24 h induction with methanol. The associated trees cluster genes with similar expression profiles across all conditions
Fig. 5
Fig. 5
Schematic representation of transcriptomic analysis of steps in the pathways involved in protein production and degradation. Significantly upregulated or downregulated genes (compared to wild-type) are depicted with an up or down arrow, respectively. A dash indicates no significant change compared to wild-type. Red indicates low secretors, consistently represented in the order of CV5, CV7 and CV14, yellow indicates mid secretors in the order of CV8, CV15 and CV16 and green indicates high secretors in the order of CV2, CV18 and CV23
Fig. 6
Fig. 6
Downregulation of expression of genes in the autophagy pathway of CV7(L) compared to wild-type. Microarray data was mapped using KEGG Mapper Search & Colour pathway. Green boxes indicate organism-specific pathways. Blue boxes show genes that are significantly downregulated. The figure was generated using the KEGG Mapper Search & Colour pathway programme (Kanehisa and Goto ; Kanehisa et al. 2012)

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