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Global analysis of transcript and protein levels across the Plasmodium falciparum life cycle

TLDR
Potentially post-transcriptionally regulated genes are identified, and families of functionally related genes were observed to share similar patterns of mRNA and protein accumulation.
Abstract
To investigate the role of post-transcriptional controls in the regulation of protein expression for the malaria parasite, Plasmodium falciparum, we have compared mRNA transcript and protein abundance levels for seven different stages of the parasite life cycle. A moderately high positive relationship between mRNA and protein abundance was observed for these stages; the most common discrepancy was a delay between mRNA and protein accumulation. Potentially post-transcriptionally regulated genes are identified, and families of functionally related genes were observed to share similar patterns of mRNA and protein accumulation.

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Journal ArticleDOI

On the Dependency of Cellular Protein Levels on mRNA Abundance.

TL;DR: It is concluded that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.
Journal ArticleDOI

Global signatures of protein and mRNA expression levels

TL;DR: This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters.
Journal ArticleDOI

A protein interaction network of the malaria parasite Plasmodium falciparum

TL;DR: From more than 32,000 yeast two-hybrid screens with P. falciparum protein fragments, 2,846 unique interactions are identified, most of which include at least one previously uncharacterized protein.
Journal ArticleDOI

Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling.

TL;DR: This molecular compendium, fully accessible via a searchable web-browser interface, serves as a reliable reference of the expressed tissue and organelle proteomes of a leading model mammal.
Journal ArticleDOI

The exopolysaccharide matrix modulates the interaction between 3D architecture and virulence of a mixed-species oral biofilm.

TL;DR: The mechanisms through which the Streptococcus mutans-produced EPS-matrix modulates the three-dimensional architecture and the population shifts during morphogenesis of biofilms on a saliva-coated-apatitic surface are explored, illustrating the critical interaction between matrix architecture and pH heterogeneity in the 3D environment.
References
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Journal ArticleDOI

An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.

TL;DR: The approach described in this manuscript provides a convenient method to interpret tandem mass spectra with known sequences in a protein database.
Proceedings Article

Fitting a mixture model by expectation maximization to discover motifs in biopolymers.

TL;DR: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences.
Journal ArticleDOI

Large-scale analysis of the yeast proteome by multidimensional protein identification technology.

TL;DR: MudPIT was applied to the proteome of the Saccharomyces cerevisiae strain BJ5460 grown to mid-log phase and yielded the largest proteome analysis to date, identifying 131 proteins with three or more predicted transmembrane domains which allowed us to map the soluble domains of many of the integral membrane proteins.
Journal ArticleDOI

Correlation between Protein and mRNA Abundance in Yeast

TL;DR: The results clearly delineate the technical boundaries of current approaches for quantitative analysis of protein expression and reveal that simple deduction from mRNA transcript analysis is insufficient to predict protein expression levels from quantitative mRNA data.
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