Quantitative iTRAQ LC–MS/MS proteomics reveals the cellular response to heterologous protein overexpression and the regulation of HAC1 in Pichia pastoris

Lin, Xiaoqiong; Liang, Shuli; Han, Sang‐Ik; Zheng, Suiping; Ye, Yanrui; Lin, Ying

doi:10.1016/j.jprot.2013.06.031

Cited by 58 publications

(44 citation statements)

References 71 publications

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“…Lin et al (2013) saw that in a low-expressing strain, five ribosome biogenesis genes were downregulated compared to nine that were upregulated in a high-expressing strain. They determined that higher expression required higher translation rates for protein synthesis.…”

Section: Discussionmentioning

confidence: 99%

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

Barton

Leak

2017

Appl Microbiol Biotechnol

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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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00253-017-8317-2) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

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

Barton

Leak

2017

Appl Microbiol Biotechnol

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“…Raw data files were converted into MGF files using the Proteome Discoverer software to generate a peak list (Lin et al, 2013). Proteins were identified and quantified using the Mascot 2.3.02 search engine (Matrix Science, London, United Kingdom) and compared against the transcriptome database of 67,177 unigene sequences.…”

Section: Methodsmentioning

confidence: 99%

Quantitative proteome-level analysis of paulownia witches’ broom disease with methyl methane sulfonate assistance reveals diverse metabolic changes during the infection and recovery processes

Wang

Liu

Fan

et al. 2017

PeerJ

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Paulownia witches’ broom (PaWB) disease caused by phytoplasma is a fatal disease that leads to considerable economic losses. Although there are a few reports describing studies of PaWB pathogenesis, the molecular mechanisms underlying phytoplasma pathogenicity in Paulownia trees remain uncharacterized. In this study, after building a transcriptome database containing 67,177 sequences, we used isobaric tags for relative and absolute quantification (iTRAQ) to quantify and analyze the proteome-level changes among healthy P. fortunei (PF), PaWB-infected P. fortunei (PFI), and PaWB-infected P. fortunei treated with 20 mg L−1 or 60 mg L−1 methyl methane sulfonate (MMS) (PFI-20 and PFI-60, respectively). A total of 2,358 proteins were identified. We investigated the proteins profiles in PF vs. PFI (infected process) and PFI-20 vs. PFI-60 (recovered process), and further found that many of the MMS-response proteins mapped to “photosynthesis” and “ribosome” pathways. Based on our comparison scheme, 36 PaWB-related proteins were revealed. Among them, 32 proteins were classified into three functional groups: (1) carbohydrate and energy metabolism, (2) protein synthesis and degradation, and (3) stress resistance. We then investigated the PaWB-related proteins involved in the infected and recovered processes, and discovered that carbohydrate and energy metabolism was inhibited, and protein synthesis and degradation decreased, as the plant responded to PaWB. Our observations may be useful for characterizing the proteome-level changes that occur at different stages of PaWB disease. The data generated in this study may serve as a valuable resource for elucidating the pathogenesis of PaWB disease during phytoplasma infection and recovery stages.

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“…change (the proteins with 1.2-fold changes relative to the normal control were based on the published reference [15,16]) with a Q-value less than 0.05, and 2) the third ratio was more than 1.0-fold change with a Q-value less than 0.05.…”

Section: Proteins Identification and Quantificationmentioning

confidence: 99%

Plasma-based proteomics reveals immune response, complement and coagulation cascades pathway shifts in heat-stressed lactating dairy cows

Cheng

Zhao

et al. 2016

Journal of Proteomics

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Quantitative iTRAQ LC–MS/MS proteomics reveals the cellular response to heterologous protein overexpression and the regulation of HAC1 in Pichia pastoris

Cited by 58 publications

References 71 publications

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

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

Quantitative proteome-level analysis of paulownia witches’ broom disease with methyl methane sulfonate assistance reveals diverse metabolic changes during the infection and recovery processes

Plasma-based proteomics reveals immune response, complement and coagulation cascades pathway shifts in heat-stressed lactating dairy cows

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