Transcriptome and Proteome Exploration to Model Translation Efficiency and Protein Stability in Lactococcus lactis

This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms

A Functional Genomics Approach to Establish the Complement of Carbohydrate Transporters in Streptococcus pneumoniae

The aerotolerant anaerobe Streptococcus pneumoniae is part of the normal nasopharyngeal microbiota of humans and one of the most important invasive pathogens. A genomic survey allowed establishing the occurrence of twenty-one phosphotransferase systems, seven carbohydrate uptake ABC transporters, one sodium∶solute symporter and a permease, underlining an exceptionally high capacity for uptake of carbohydrate substrates. Despite high genomic variability, combined phenotypic and genomic analysis of twenty sequenced strains did assign the substrate specificity only to two uptake systems. Systematic analysis of mutants for most carbohydrate transporters enabled us to assign a phenotype and substrate specificity to twenty-three transport systems. For five putative transporters for galactose, pentoses, ribonucleosides and sulphated glycans activity was inferred, but not experimentally confirmed and only one transport system remains with an unknown substrate and lack of any functional annotation. Using a metabolic approach, 80% of the thirty-two fermentable carbon substrates were assigned to the corresponding transporter. The complexity and robustness of sugar uptake is underlined by the finding that many transporters have multiple substrates, and many sugars are transported by more than one system. The present work permits to draw a functional map of the complete arsenal of carbohydrate utilisation proteins of pneumococci, allows re-annotation of genomic data and might serve as a reference for related species. These data provide tools for specific investigation of the roles of the different carbon substrates on pneumococcal physiology in the host during carriage and invasive infection

Rewiring Lactococcus lactis for Ethanol Production

Lactic acid bacteria (LAB) are known for their high tolerance toward organic acids and alcohols (R. S. Gold, M. M. Meagher, R. Hutkins, and T. Conway, J. Ind. Microbiol. 10:45–54, 1992) and could potentially serve as platform organisms for production of these compounds. In this study, we attempted to redirect the metabolism of LAB model organism Lactococcus lactis toward ethanol production. Codon-optimized Zymomonas mobilis pyruvate decarboxylase (PDC) was introduced and expressed from synthetic promoters in different strain backgrounds. In the wild-type L. lactis strain MG1363 growing on glucose, only small amounts of ethanol were obtained after introducing PDC, probably due to a low native alcohol dehydrogenase activity. When the same strains were grown on maltose, ethanol was the major product and lesser amounts of lactate, formate, and acetate were formed. Inactivating the lactate dehydrogenase genes ldhX, ldhB, and ldh and introducing codon-optimized Z. mobilis alcohol dehydrogenase (ADHB) in addition to PDC resulted in high-yield ethanol formation when strains were grown on glucose, with only minor amounts of by-products formed. Finally, a strain with ethanol as the sole observed fermentation product was obtained by further inactivating the phosphotransacetylase (PTA) and the native alcohol dehydrogenase (ADHE)

Role of bacterial peptidase F inferred by statistical analysis and further experimental validation

Despite the quantity of high-throughput data available nowadays, the precise role of many proteins has not been elucidated. Available methods for classifying proteins and reconstructing metabolic networks are efficient for finding global categories, but do not answer the biologist’s specific and targeted questions. Following Yamanishi et al. [Yamanishi, Y, Vert, JP, Nakaya, A, and Kaneisha, M (2003). “Extraction of correlated clusters from multiple genomic data by generalized kernel canonical correlation analysis.” Bioinformatics 19, Suppl. 1, i323–i330] we used a kernel canonical correlation analysis (KCCA) to predict the role of the bacterial peptidase PepF. We integrated five existing data types: protein metabolic networks, microarray data, phylogenetic profiles, distances between proteins and incomplete two-dimensional-gel data (for which we propose a completion strategy), available for Lactococcus lactis to determine relationships between proteins. The predicted relationships were then used to guide our laboratory work which proved most of the predictions correct. PepF had previously been characterized as a zinc dependent endopeptidase [Nardi, M, Renault, P, and Monnet, V (1997). “Duplication of the pepF gene and shuffling of DNA fragments on the lactose plasmid of Lactococcus lactis.” J. Bacteriol. 179, 4164–4171; Monnet, V, Nardi, M, Chopin, MC, and Gripon, JC (1994). “Biochemical and genetic characterization of PepF on oligoendopeptidase from Lactococcus lactis.” J. Bio. Chem. 269, 32070–32076]. Analyzing a PepF mutant, we confirmed its participation in protein secretion through a strong relationship between the signal peptidase I and PepF predicted by the KCCA. The global nature of our approach made it possible to discover pleiotropic roles of the protein which had remained unknown using classical approaches