Overexpression of Arabidopsis Ceramide Synthases Differentially Affects Growth, Sphingolipid Metabolism, Programmed Cell Death, and Mycotoxin Resistance.

Ceramide synthases catalyze an N-acyltransferase reaction using fatty acyl-coenzyme A (CoA) and long-chain base (LCB) substrates to form the sphingolipid ceramide backbone and are targets for inhibition by the mycotoxin fumonisin B1 (FB1). Arabidopsis (Arabidopsis thaliana) contains three genes encoding ceramide synthases with distinct substrate specificities: LONGEVITY ASSURANCE GENE ONE HOMOLOG1 (LOH1; At3g25540)- and LOH3 (At1g19260)-encoded ceramide synthases use very-long-chain fatty acyl-CoA and trihydroxy LCB substrates, and LOH2 (At3g19260)-encoded ceramide synthase uses palmitoyl-CoA and dihydroxy LCB substrates. In this study, complementary DNAs for each gene were overexpressed to determine the role of individual isoforms in physiology and sphingolipid metabolism. Differences were observed in growth resulting from LOH1 and LOH3 overexpression compared with LOH2 overexpression. LOH1- and LOH3-overexpressing plants had enhanced biomass relative to wild-type plants, due in part to increased cell division, suggesting that enhanced synthesis of very-long-chain fatty acid/trihydroxy LCB ceramides promotes cell division and growth. Conversely, LOH2 overexpression resulted in dwarfing. LOH2 overexpression also resulted in the accumulation of sphingolipids with C16 fatty acid/dihydroxy LCB ceramides, constitutive induction of programmed cell death, and accumulation of salicylic acid, closely mimicking phenotypes observed previously in LCB C-4 hydroxylase mutants defective in trihydroxy LCB synthesis. In addition, LOH2- and LOH3-overexpressing plants acquired increased resistance to FB1, whereas LOH1-overexpressing plants showed no increase in FB1 resistance, compared with wild-type plants, indicating that LOH1 ceramide synthase is most strongly inhibited by FB1. Overall, the findings described here demonstrate that overexpression of Arabidopsis ceramide synthases results in strongly divergent physiological and metabolic phenotypes, some of which have significance for improved plant performance.

An algorithmic framework for genome-wide modeling and analysis of translation networks.

The sequencing of genomes of several organisms and advances in high throughput technologies for transcriptome and proteome analysis has allowed detailed mechanistic studies of transcription and translation using mathematical frameworks that allow integration of both sequence-specific and kinetic properties of these fundamental cellular processes. To understand how perturbations in mRNA levels affect the synthesis of individual proteins within a large protein synthesis network, we consider here a genome-scale codon-wide model of the translation machinery with explicit description of the processes of initiation, elongation, and termination. The mechanistic codon-wide description of the translation process and the large number of mRNAs competing for resources, such as ribosomes, requires the use of novel efficient algorithmic approaches. We have developed such an efficient algorithmic framework for genome-scale models of protein synthesis. The mathematical and computational framework was applied to the analysis of the sensitivity of a translation network to perturbation in the rate constants and in the mRNA levels in the system. Our studies suggest that the highest specific protein synthesis rate (protein synthesis rate per mRNA molecule) is achieved when translation is elongation-limited. We find that the mRNA species with the highest number of actively translating ribosomes exerts maximum control on the synthesis of every protein, and the response of protein synthesis rates to mRNA expression variation is a function of the strength of initiation of translation at different mRNA species. Such quantitative understanding of the sensitivity of protein synthesis to the variation of mRNA expression can provide insights into cellular robustness mechanisms and guide the design of protein production systems.

Insights into the relation between mRNA and protein expression patterns: I. Theoretical considerations.

Translation is a central cellular process in every organism and understanding translation from the systems (genome-wide) perspective is very important for medical and biochemical engineering applications. Moreover, recent advances in cell-wide monitoring tools for both mRNA and protein levels have necessitated the development of such a model to identify parameters and conditions that influence the mapping between mRNA and protein expression. Experimental studies show a lack of correspondence between mRNA and protein expression profiles. In this study, we describe a mechanistic genome-wide model for translation that provides mapping between changes in mRNA levels and changes in protein levels. We use our model to study the system in detail and identify the key parameters that affect this mapping. Our results show that the correlation between mRNA and protein levels is a function of both the kinetic parameters and concentration of ribosomes at the reference state. In particular, changes in concentration of free and total ribosomes in response to a perturbation; changes in initiation and elongation kinetics due to competition for aminoacyl tRNAs; changes in termination kinetics; average changes in mRNA levels in response to the perturbation; and changes in protein stability are all important determinants of the mapping between mRNA and protein expression.

Insights into the relation between mrna and protein expression patterns: II. Experimental observations in Escherichia coli.

There is a need for improved appreciation of the importance of genome-wide mRNA and protein expression measurements and their role in understanding translation and in relation to genome-wide mathematical frameworks for gene expression regulation. We investigated the use of a high-density microarray technique for mRNA expression analysis and a two-dimensional protein electrophoresis-tandem mass spectrometry method for protein analysis to monitor changes in gene expression. We applied these analytical tools in the context of an environmental perturbation of Escherichia coli cells-the addition of varying amounts of IPTG. We also tested the application of these tools to the study of a genetic perturbation of Escherichia coli cells-the ability of certain strains to hypersecrete the hemolysin protein. We observed a lack of correspondence between mRNA and protein expression profiles. Although our data do not include measurements on all expressed genes (because the ability to measure protein expression profiles is limiting), we observed that the qualitative and quantitative behavior of the measurements of a subset of expressed genes is similar to the behavior of the entire system. The change in observed average mRNA and protein amplification factors for 77 and 52 genes coincided with the observed change in mRNA amplification factor for the entire system. Furthermore, we found that the use of relative changes in expression could be used to elucidate mechanisms of gene expression regulation for the system studied, even when measurements were made on a small subset of the system.