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Comparative genomics and transcriptomics of Pichia pastoris

Overview of attention for article published in BMC Genomics, August 2016
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Title
Comparative genomics and transcriptomics of Pichia pastoris
Published in
BMC Genomics, August 2016
DOI 10.1186/s12864-016-2876-y
Pubmed ID
Authors

Kerry R. Love, Kartik A. Shah, Charles A. Whittaker, Jie Wu, M. Catherine Bartlett, Duanduan Ma, Rachel L. Leeson, Margaret Priest, Jonathan Borowsky, Sarah K. Young, J. Christopher Love

Abstract

Pichia pastoris has emerged as an important alternative host for producing recombinant biopharmaceuticals, owing to its high cultivation density, low host cell protein burden, and the development of strains with humanized glycosylation. Despite its demonstrated utility, relatively little strain engineering has been performed to improve Pichia, due in part to the limited number and inconsistent frameworks of reported genomes and transcriptomes. Furthermore, the co-mingling of genomic, transcriptomic and fermentation data collected about Komagataella pastoris and Komagataella phaffii, the two strains co-branded as Pichia, has generated confusion about host performance for these genetically distinct species. Generation of comparative high-quality genomes and transcriptomes will enable meaningful comparisons between the organisms, and potentially inform distinct biotechnological utilies for each species. Here, we present a comprehensive and standardized comparative analysis of the genomic features of the three most commonly used strains comprising the tradename Pichia: K. pastoris wild-type, K. phaffii wild-type, and K. phaffii GS115. We used a combination of long-read (PacBio) and short-read (Illumina) sequencing technologies to achieve over 1000X coverage of each genome. Construction of individual genomes was then performed using as few as seven individual contigs to create gap-free assemblies. We found substantial syntenic rearrangements between the species and characterized a linear plasmid present in K. phaffii. Comparative analyses between K. phaffii genomes enabled the characterization of the mutational landscape of the GS115 strain. We identified and examined 35 non-synonomous coding mutations present in GS115, many of which are likely to impact strain performance. Additionally, we investigated transcriptomic profiles of gene expression for both species during cultivation on various carbon sources. We observed that the most highly transcribed genes in both organisms were consistently highly expressed in all three carbon sources examined. We also observed selective expression of certain genes in each carbon source, including many sequences not previously reported as promoters for expression of heterologous proteins in yeasts. Our studies establish a foundation for understanding critical relationships between genome structure, cultivation conditions and gene expression. The resources we report here will inform and facilitate rational, organism-wide strain engineering for improved utility as a host for protein production.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 205 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 <1%
Spain 1 <1%
Germany 1 <1%
Austria 1 <1%
Unknown 201 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 20%
Researcher 34 17%
Student > Master 29 14%
Student > Bachelor 20 10%
Student > Postgraduate 12 6%
Other 22 11%
Unknown 46 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 74 36%
Agricultural and Biological Sciences 45 22%
Engineering 10 5%
Chemical Engineering 6 3%
Immunology and Microbiology 4 2%
Other 14 7%
Unknown 52 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 August 2016.
All research outputs
#12,768,290
of 22,881,964 outputs
Outputs from BMC Genomics
#4,411
of 10,668 outputs
Outputs of similar age
#187,741
of 366,897 outputs
Outputs of similar age from BMC Genomics
#102
of 271 outputs
Altmetric has tracked 22,881,964 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 366,897 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 271 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.