Dataset Information

Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains.

ABSTRACT: Incorporation of strain-specific synthetic DNA tags into yeast Saccharomyces cerevisiae gene-deletion strains has enabled identification of gene functions by massively parallel growth rate analysis. However, it is important to confirm the sequences of these tags, because mutations introduced during construction could lead to significant errors in hybridization performance. To validate this experimental system, we sequenced 11,812 synthetic 20-mer molecular bar codes and adjacent sequences (>1.8 megabases synthetic DNA) by pyrosequencing and Sanger methods. At least 31% of the genome-integrated 20-mer tags contain differences from those originally synthesized. However, these mutations result in anomalous hybridization in only a small subset of strains, and the sequence information enables redesign of hybridization probes for arrays. The robust performance of the yeast gene-deletion dual oligonucleotide bar-code design in array hybridization validates the use of molecular bar codes in living cells for tracking their growth phenotype.

SUBMITTER: Eason RG

PROVIDER: S-EPMC491991 | biostudies-literature | 2004 Jul

REPOSITORIES: biostudies-literature

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Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains.

Eason Robert G RG Pourmand Nader N Tongprasit Waraporn W Herman Zelek S ZS Anthony Kevin K Jejelowo Olufisayo O Davis Ronald W RW Stolc Viktor V

Proceedings of the National Academy of Sciences of the United States of America 20040716 30

Incorporation of strain-specific synthetic DNA tags into yeast Saccharomyces cerevisiae gene-deletion strains has enabled identification of gene functions by massively parallel growth rate analysis. However, it is important to confirm the sequences of these tags, because mutations introduced during construction could lead to significant errors in hybridization performance. To validate this experimental system, we sequenced 11,812 synthetic 20-mer molecular bar codes and adjacent sequences (>1.8 ...[more]

PMID: 15258289

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Project description:BackgroundMobile Genetic Elements (MGEs) are selfish DNA integrated in the genomes. Their detection is mainly based on consensus-like searches by scanning the investigated genome against the sequence of an already identified MGE. Mobilomics aims at discovering all the MGEs in a genome and understanding their dynamic behavior: The data for this kind of investigation can be provided by comparative genomics of closely related organisms. The amount of data thus involved requires a strong computational effort, which should be alleviated.ResultsOur approach proposes to exploit the high similarity among homologous chromosomes of different strains of the same species, following a progressive comparative genomics philosophy. We introduce a software tool based on our new fast algorithm, called regender, which is able to identify the conserved regions between chromosomes. Our case study is represented by a unique recently available dataset of 39 different strains of S.cerevisiae, which regender is able to compare in few minutes. By exploring the non-conserved regions, where MGEs are mainly retrotransposons called Tys, and marking the candidate Tys based on their length, we are able to locate a priori and automatically all the already known Tys and map all the putative Tys in all the strains. The remaining putative mobile elements (PMEs) emerging from this intra-specific comparison are sharp markers of inter-specific evolution: indeed, many events of non-conservation among different yeast strains correspond to PMEs. A clustering based on the presence/absence of the candidate Tys in the strains suggests an evolutionary interconnection that is very similar to classic phylogenetic trees based on SNPs analysis, even though it is computed without using phylogenetic information.ConclusionsThe case study indicates that the proposed methodology brings two major advantages: (a) it does not require any template sequence for the wanted MGEs and (b) it can be applied to infer MGEs also for low coverage genomes with unresolved bases, where traditional approaches are largely ineffective.

Project description:BackgroundDespite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance.ResultsWe find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses.ConclusionsOur results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.

Dataset Information

Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains.

Publications

Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains.

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