Dataset Information

Genome-Wide Determination of Gene Essentiality by Transposon Insertion Sequencing in Yeast Pichia pastoris.

ABSTRACT: In many prokaryotes but limited eukaryotic species, the combination of transposon mutagenesis and high-throughput sequencing has greatly accelerated the identification of essential genes. Here we successfully applied this technique to the methylotrophic yeast Pichia pastoris and classified its conditionally essential/non-essential gene sets. Firstly, we showed that two DNA transposons, TcBuster and Sleeping beauty, had high transposition activities in P. pastoris. By merging their insertion libraries and performing Tn-seq, we identified a total of 202,858 unique insertions under glucose supported growth condition. We then developed a machine learning method to classify the 5,040 annotated genes into putatively essential, putatively non-essential, ambig1 and ambig2 groups, and validated the accuracy of this classification model. Besides, Tn-seq was also performed under methanol supported growth condition and methanol specific essential genes were identified. The comparison of conditionally essential genes between glucose and methanol supported growth conditions helped to reveal potential novel targets involved in methanol metabolism and signaling. Our findings suggest that transposon mutagenesis and Tn-seq could be applied in the methylotrophic yeast Pichia pastoris to classify conditionally essential/non-essential gene sets. Our work also shows that determining gene essentiality under different culture conditions could help to screen for novel functional components specifically involved in methanol metabolism.

SUBMITTER: Zhu J

PROVIDER: S-EPMC6033949 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-Wide Determination of Gene Essentiality by Transposon Insertion Sequencing in Yeast Pichia pastoris.

Zhu Jinxiang J Gong Ruiqing R Zhu Qiaoyun Q He Qiulin Q Xu Ning N Xu Yichun Y Cai Menghao M Zhou Xiangshan X Zhang Yuanxing Y Zhou Mian M

Scientific reports 20180705 1

In many prokaryotes but limited eukaryotic species, the combination of transposon mutagenesis and high-throughput sequencing has greatly accelerated the identification of essential genes. Here we successfully applied this technique to the methylotrophic yeast Pichia pastoris and classified its conditionally essential/non-essential gene sets. Firstly, we showed that two DNA transposons, TcBuster and Sleeping beauty, had high transposition activities in P. pastoris. By merging their insertion libr ...[more]

PMID: 29976927

Similar Datasets

Project description:Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses.IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen Edwardsiella piscicida. PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a terminal sampling point, and its clustering of mutants with related fitness profiles informed design of new live vaccine candidates. PACE yields insights into patterns of fitness dynamics and circumvents major limitations of existing methodologies. Finally, the PACE method should be applicable to additional "omic" time series data, including screens based on clustered regularly interspaced short palindromic repeats with Cas9 (CRISPR/Cas9).

Project description:Mycobacterium abscessus is an emerging opportunistic human pathogen that naturally resists most major classes of antibiotics, making infections difficult to treat. Thus far, little is known about M. abscessus physiology, pathogenesis, and drug resistance. Genome-wide analyses have comprehensively catalogued genes with essential functions in Mycobacterium tuberculosis and Mycobacterium avium subsp. hominissuis (here, M. avium) but not in M. abscessus. By optimizing transduction conditions, we achieved full saturation of TA insertion sites with Himar1 transposon mutagenesis in the M. abscessus ATCC 19977T genome, as confirmed by deep sequencing prior to essentiality analyses of annotated genes and other genomic features. The overall densities of inserted TA sites (85.7%), unoccupied TA sites (14.3%), and nonpermissive TA sites (8.1%) were similar to results in M. tuberculosis and M. avium. Of the 4,920 annotated genes, 326 were identified as essential, 269 (83%) of which have mutual homology with essential M. tuberculosis genes, while 39 (12%) are homologous to genes that are not essential in M. tuberculosis and M. avium, and 11 (3.4%) only have homologs in M. avium. Interestingly, 7 (2.1%) essential M. abscessus genes have no homologs in either M. tuberculosis or M. avium, two of which were found in phage-like elements. Most essential genes are involved in DNA replication, RNA transcription and translation, and posttranslational events to synthesize important macromolecules. Some essential genes may be involved in M. abscessus pathogenesis and antibiotics response, including certain essential tRNAs and new short open reading frames. Our findings will help to pave the way for better understanding of M. abscessus and benefit development of novel bactericidal drugs against M. abscessus. IMPORTANCE Limited knowledge regarding Mycobacterium abscessus pathogenesis and intrinsic resistance to most classes of antibiotics is a major obstacle to developing more effective strategies to prevent and mitigate disease. Using optimized procedures for Himar1 transposon mutagenesis and deep sequencing, we performed a comprehensive analysis to identify M. abscessus genetic elements essential for in vitro growth and compare them to similar data sets for M. tuberculosis and M. avium subsp. hominissuis. Most essential M. abscessus genes have mutual homology with essential M. tuberculosis genes, providing a foundation for leveraging available knowledge from M. tuberculosis to develop more effective drugs and other interventions against M. abscessus. A small number of essential genes unique to M. abscessus deserve further attention to gain insights into what makes M. abscessus different from other mycobacteria. The essential genes and other genomic features such as short open reading frames and noncoding RNA identified here will provide useful information for future study of M. abscessus pathogenicity and new drug development.

Project description:BackgroundPichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.ResultsA fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified.ConclusionThe genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

Dataset Information

Genome-Wide Determination of Gene Essentiality by Transposon Insertion Sequencing in Yeast Pichia pastoris.

Publications

Genome-Wide Determination of Gene Essentiality by Transposon Insertion Sequencing in Yeast Pichia pastoris.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets